Selecting And Correlating Physical Activity Data With Image Data

ABSTRACT

Example embodiments may relate systems, methods, apparatuses, and computer readable media configured to correlate image data of a user performing physical activity with data collected during the user&#39;s performance. Data may include sensor data measuring, force, acceleration, speed, and/or processed sensor data from one or more sensors. Certain embodiments may determine whether the user is within a performance zone based on user attributes. Correlation of the image data with physical activity data may be based, at least in part, whether the user is within a performance zone.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of and is a continuation of U.S.patent application Ser. No. 13/399452 filed Feb. 17, 2012, titled“Selecting and Correlating Physical Activity Data with Image Data,”which claims the benefit of and priority to, U.S. Provisional Patent No.61/443,808 filed Feb. 17, 2011, titled “Tracking of User PerformanceMetrics During a Workout Session.” The contents of the above notedapplications are incorporated herein by reference herein in theirentirety for any and all non-limiting purposes.

BACKGROUND

Exercise and fitness have become increasingly popular and the benefitsfrom such activities are well known. Various types of technology havebeen incorporated into fitness and other athletic activities. Forexample, a wide variety of portable electronic devices are available foruse in fitness activity such as MP3 or other audio players, radios,portable televisions, DVD players, or other video playing devices,watches, GPS systems, pedometers, mobile telephones, pagers, beepers,etc. Many fitness enthusiasts or athletes use one or more of thesedevices when exercising or training to keep them entertained, provideperformance data or to keep them in contact with others, etc. Such usershave also demonstrated an interest in recording their athleticactivities and metrics associated therewith. Accordingly, varioussensors may be used to detect, store and/or transmit athleticperformance information. Oftentimes, however, athletic performanceinformation is presented in a vacuum or based on the overall athleticactivity. Exercisers may be interested in obtaining additionalinformation about their workouts.

SUMMARY

The following presents a general summary of example aspects to provide abasic understanding of example embodiments. This summary is not anextensive overview. It is not intended to identify key or criticalelements or to delineate scope of the invention. The following summarymerely presents some concepts of the invention in a general form as aprelude to the more detailed description provided below.

One or more aspects describe systems, apparatuses, computer readablemedia, and methods for tracking performance metrics of a user during anexercise session.

In some example aspects, the systems, apparatuses, computer readablemedia, and methods may be configured to process input specifying a userattribute, adjust a performance zone based on the user attribute,receive data generated by at least one of an accelerometer and a forcesensor, determine whether the data is within the performance zone, andoutput the determination.

In some example aspects, the systems, apparatuses, computer readablemedia, and methods may include receiving data generated by a sensor(e.g., an accelerometer, a force sensor, temperature sensor, heart ratemonitor, etc.) as a user performs an athletic movement, and comparingthe data with comparison data of a plurality of playing styles todetermine a particular one of the playing styles most closely matchingthe data.

In some example aspects, the systems, apparatuses, computer readablemedia, and methods may include receiving data generated by a forcesensor indicating a weight distribution during a performance of aplurality of exercise tasks, processing first input indicatingsuccessful completion of an exercise task, associating a first weightdistribution at a time preceding the first input with the successfulcompletion of the exercise task, processing second input indicatingunsuccessful completion of the exercise task, and associating a secondweight distribution at a time preceding the second input with theunsuccessful completion of the exercise task.

In some example aspects, the systems, apparatuses, computer readablemedia, and methods may include receiving signature move datacorresponding to acceleration and force measurement data measured by afirst user performing a sequence of events, receiving player data fromat least one of an accelerometer and a force sensor by monitoring asecond user attempting to perform the sequence of events, and generatinga similarity metric indicating how similar the player data is to thesignature move data.

In some example aspects, the systems, apparatuses, computer readablemedia, and methods may include receiving data generated by at least oneof an accelerometer and a force sensor, comparing the data to jump datato determine that the data is consistent with a jump, processing thedata to determine a lift off time, a landing time, and a loft time, andcalculating a vertical leap based on the loft time.

Other aspects and features are described throughout the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

To understand the example embodiments, it will now be described by wayof example, with reference to the accompanying drawings in which:

FIGS. 1A-B illustrate an example of a personal training system inaccordance with example embodiments.

FIGS. 2A-B illustrate example embodiments of a sensor system inaccordance with example embodiments.

FIGS. 3A-B illustrate an example of a computer interacting with at leastone sensor in accordance with example embodiments.

FIGS. 4A-B illustrate examples of pod sensors that may be embedded andremoved from a shoe in accordance with example embodiments.

FIG. 5 illustrates example on-body configurations for a computer inaccordance with example embodiments.

FIGS. 6-7 illustrates example various off-body configurations for acomputer in accordance with example embodiments.

FIG. 8 illustrates an example display of a graphical user interface(GUI) presented by a display screen of a computer in accordance withexample embodiments.

FIG. 9 illustrates example performance metrics for user selection inaccordance with example embodiments.

FIGS. 10A-C illustrate an example of calibrating sensors in accordancewith example embodiments.

FIGS. 11A-B illustrate an example of calibrating sensors in accordancewith example embodiments.

FIGS. 11C-D illustrate example displays of a GUI presenting informationrelating to an example calibration of sensors in accordance with exampleembodiments.

FIGS. 12A-D illustrate example displays of a GUI presenting informationrelative to a session in accordance with example embodiments.

FIG. 13 illustrates an example display of a GUI providing a user withinformation about their performance metrics during a session inaccordance with example embodiments.

FIGS. 14A-C illustrate example displays of a GUI presenting informationabout a user's virtual card (vcard) in accordance with exampleembodiments.

FIG. 15 illustrates an example user profile display of a GUI presentinga user profile in accordance with example embodiments.

FIG. 16 illustrates a further example of user profile display presentingadditional information about the user in accordance with exampleembodiments.

FIGS. 17A-D illustrate further example displays of a GUI for displayingperformance metrics to a user in accordance with example embodiments.

FIGS. 18A-C illustrate further example displays of a GUI for displayingperformance metrics to a user in accordance with example embodiments

FIGS. 19A-D illustrate further example displays of a GUI for displayingperformance metrics to a user in accordance with example embodiments

FIGS. 20A-B illustrate further example displays of a GUI for displayingperformance metrics to a user in accordance with example embodiments.

FIGS. 21A-C illustrate example freestyle displays of a GUI providinginformation on freestyle user movement in accordance with exampleembodiments.

FIGS. 22A-B illustrate example training displays presentinguser-selectable training sessions in accordance with exampleembodiments.

FIGS. 23-26 illustrate example training sessions in accordance withexample embodiments.

FIG. 27 illustrates a display screen for GUIs for a basketball shootingtraining session in accordance with example embodiments.

FIGS. 28A-C illustrate display screen for GUIs for a basketball shootingtraining session in accordance with example embodiments.

FIGS. 29A-B illustrate display screen for GUIs for a basketball shootingtraining session in accordance with example embodiments.

FIGS. 30A-C illustrate display screen for GUIs for a basketball shootingtraining session in accordance with example embodiments.

FIG. 31 illustrates an example display of a GUI informing the user ofshooting milestones in accordance with example embodiments.

FIGS. 32A-C illustrate example signature moves displays for a GUIprompting a user to perform a drill to imitate a professional athlete'ssignature move in accordance with example embodiments.

FIGS. 33A-C illustrate example displays of a GUI for searching for otherusers and/or professional athletes for comparison of performance metricsin accordance with example embodiments.

FIGS. 34A-B illustrate example displays for comparing a user'sperformance metrics to other individuals in accordance with exampleembodiments.

FIGS. 35A-B illustrate example displays for comparing a user'sperformance metrics to other individuals in accordance with exampleembodiments.

FIG. 36 illustrates a flow diagram of an example method for determiningwhether physical data obtained monitoring a user performing a physicalactivity is within a performance zone in accordance with exampleembodiments.

FIG. 37 illustrates a flow diagram of an example method of correlatingimage data and forming a collection of images that may be utilized inaccordance with e embodiments.

DETAILED DESCRIPTION

In the following description of the various embodiments, reference ismade to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration various embodiments in which thedisclosure may be practiced. It is to be understood that otherembodiments may be utilized and structural and functional modificationsmay be made without departing from the scope and spirit of the presentdisclosure. Further, headings within this disclosure should not beconsidered as limiting aspects of the disclosure. Those skilled in theart with the benefit of this disclosure will appreciate that the exampleembodiments are not limited to the example headings.

I. Example Personal Training System

A. Illustrative Computing Devices

FIG. 1A illustrates an example of a personal training system 100 inaccordance with example embodiments. Example system 100 may include oneor more electronic devices, such as computer 102. Computer 102 maycomprise a mobile terminal, such as a telephone, music player, tablet,netbook or any portable device. In other embodiments, computer 102 maycomprise a set-top box (STB), desktop computer, digital videorecorder(s) (DVR), computer server(s), and/or any other desiredcomputing device. In certain configurations, computer 102 may comprise agaming console, such as for example, a Microsoft® XBOX, Sony®Playstation, and/or a Nintendo® Wii gaming consoles. Those skilled inthe art will appreciate that these are merely example consoles fordescriptive purposes and this disclosure is not limited to any consoleor device.

Turning briefly to FIG. 1B, computer 102 may include computing unit 104,which may comprise at least one processing unit 106. Processing unit 106may be any type of processing device for executing softwareinstructions, such as for example, a microprocessor device. Computer 102may include a variety of non-transitory computer readable media, such asmemory 108. Memory 108 may include, but is not limited to, random accessmemory (RAM) such as RAM 110, and/or read only memory (ROM), such as ROM112. Memory 108 may include any of: electronically erasable programmableread only memory (EEPROM), flash memory or other memory technology,CD-ROM, digital versatile disks (DVD) or other optical disk storage,magnetic storage devices, or any other medium that can be used to storethe desired information and that can be accessed by computer 102.

The processing unit 106 and the system memory 108 may be connected,either directly or indirectly, through a bus 114 or alternatecommunication structure to one or more peripheral devices. For example,the processing unit 106 or the system memory 108 may be directly orindirectly connected to additional memory storage, such as a hard diskdrive 116, a removable magnetic disk drive, an optical disk drive 118,and a flash memory card. The processing unit 106 and the system memory108 also may be directly or indirectly connected to one or more inputdevices 120 and one or more output devices 122. The output devices 122may include, for example, a display device 136, television, printer,stereo, or speakers. In some embodiments one or more display devices maybe incorporated into eyewear. The display devices incorporated intoeyewear may provide feedback to users. Eyewear incorporating one or moredisplay devices also provides for a portable display system. The inputdevices 120 may include, for example, a keyboard, touch screen, a remotecontrol pad, a pointing device (such as a mouse, touchpad, stylus,trackball, or joystick), a scanner, a camera or a microphone. In thisregard, input devices 120 may comprise one or more sensors configured tosense, detect, and/or measure athletic movement from a user, such asuser 124, shown in FIG. 1A.

Looking again to FIG. 1A, image-capturing device 126 and/or sensor 128may be utilized in detecting and/or measuring athletic movements of user124. In one embodiment, data obtained from image-capturing device 126 orsensor 128 may directly detect athletic movements, such that the dataobtained from image-capturing device 126 or sensor 128 is directlycorrelated to a motion parameter. Yet, in other embodiments, data fromimage-capturing device 126 and/or sensor 128 may be utilized incombination, either with each other or with other sensors to detectand/or measure movements. Thus, certain measurements may be determinedfrom combining data obtained from two or more devices. Image-capturingdevice 126 and/or sensor 128 may include or be operatively connected toone or more sensors, including but not limited to: an accelerometer, agyroscope, a location-determining device (e.g., GPS), light sensor,temperature sensor (including ambient temperature and/or bodytemperature), heart rate monitor, image-capturing sensor, moisturesensor and/or combinations thereof. Example uses of illustrative sensors126, 128 are provided below in Section I.C, entitled “IllustrativeSensors.” Computer 102 may also use touch screens or image capturingdevice to determine where a user is pointing to make selections from agraphical user interface. One or more embodiments may utilize one ormore wired and/or wireless technologies, alone or in combination,wherein examples of wireless technologies include Bluetooth®technologies, Bluetooth® low energy technologies, and/or ANTtechnologies.

B. Illustrative Network

Computer 102, computing unit 104, and/or any other electronic devicesmay be directly or indirectly connected to one or more networkinterfaces, such as example interface 130 (shown in FIG. 1B) forcommunicating with a network, such as network 132. In the example ofFIG. 1B, network interface 130, may comprise a network adapter ornetwork interface card (NIC) configured to translate data and controlsignals from the computing unit 104 into network messages according toone or more communication protocols, such as the Transmission ControlProtocol (TCP), the Internet Protocol (IP), and the User DatagramProtocol (UDP). These protocols are well known in the art, and thus willnot be discussed here in more detail. An interface 130 may employ anysuitable connection agent for connecting to a network, including, forexample, a wireless transceiver, a power line adapter, a modem, or anEthernet connection. Network 132, however, may be any one or moreinformation distribution network(s), of any type(s) or topology(s),alone or in combination(s), such as internet(s), intranet(s), cloud(s),LAN(s). Network 132 may be any one or more of cable, fiber, satellite,telephone, cellular, wireless, etc. Networks are well known in the art,and thus will not be discussed here in more detail. Network 132 may bevariously configured such as having one or more wired or wirelesscommunication channels to connect one or more locations (e.g., schools,businesses, homes, consumer dwellings, network resources, etc.), to oneor more remote servers 134, or to other computers, such as similar oridentical to computer 102. Indeed, system 100 may include more than oneinstance of each component (e.g., more than one computer 102, more thanone display 136, etc.).

Regardless of whether computer 102 or other electronic device withinnetwork 132 is portable or at a fixed location, it should be appreciatedthat, in addition to the input, output and storage peripheral devicesspecifically listed above, the computing device may be connected, suchas either directly, or through network 132 to a variety of otherperipheral devices, including some that may perform input, output andstorage functions, or some combination thereof. In certain embodiments,a single device may integrate one or more components shown in FIG. 1A.For example, a single device may include computer 102, image-capturingdevice 126, sensor 128, display 136 and/or additional components. In oneembodiment, sensor device 138 may comprise a mobile terminal having adisplay 136, image-capturing device 126, and one or more sensors 128.Yet, in another embodiment, image-capturing device 126, and/or sensor128 may be peripherals configured to be operatively connected to a mediadevice, including for example, a gaming or media system. Thus, it goesfrom the foregoing that this disclosure is not limited to stationarysystems and methods. Rather, certain embodiments may be carried out by auser 124 in almost any location.

C. Illustrative Sensors

Computer 102 and/or other devices may comprise one or more sensors 126,128 configured to detect and/or monitor at least one fitness parameterof a user 124. Sensors 126 and/or 128 may include, but are not limitedto: an accelerometer, a gyroscope, a location-determining device (e.g.,GPS), light sensor, temperature sensor (including ambient temperatureand/or body temperature), sleep pattern sensors, heart rate monitor,image-capturing sensor, moisture sensor and/or combinations thereof.Network 132 and/or computer 102 may be in communication with one or moreelectronic devices of system 100, including for example, display 136, animage capturing device 126 (e.g., one or more video cameras), and sensor128, which may be an infrared (IR) device. In one embodiment sensor 128may comprise an IR transceiver. For example, sensors 126, and/or 128 maytransmit waveforms into the environment, including towards the directionof user 124 and receive a “reflection” or otherwise detect alterationsof those released waveforms. In yet another embodiment, image-capturingdevice 126 and/or sensor 128 may be configured to transmit and/orreceive other wireless signals, such as radar, sonar, and/or audibleinformation. Those skilled in the art will readily appreciate thatsignals corresponding to a multitude of different data spectrums may beutilized in accordance with various embodiments. In this regard, sensors126 and/or 128 may detect waveforms emitted from external sources (e.g.,not system 100). For example, sensors 126 and/or 128 may detect heatbeing emitted from user 124 and/or the surrounding environment. Thus,image-capturing device 126 and/or sensor 128 may comprise one or morethermal imaging devices. In one embodiment, image-capturing device 126and/or sensor 128 may comprise an IR device configured to perform rangephenomenology. As a non-limited example, image-capturing devicesconfigured to perform range phenomenology are commercially availablefrom Flir Systems, Inc. of Portland, Oreg. Although image capturingdevice 126 and sensor 128 and display 136 are shown in direct(wirelessly or wired) communication with computer 102, those skilled inthe art will appreciate that any may directly communicate (wirelessly orwired) with network 132.

1. Multi-Purpose Electronic Devices

User 124 may possess, carry, and/or wear any number of electronicdevices, including sensory devices 138, 140, 142, and/or 144. In certainembodiments, one or more devices 138, 140, 142, 144 may not be speciallymanufactured for fitness or athletic purposes. Indeed, aspects of thisdisclosure relate to utilizing data from a plurality of devices, some ofwhich are not fitness devices, to collect, detect, and/or measureathletic data. In one embodiment, device 138 may comprise a portableelectronic device, such as a telephone or digital music player,including an IPOD®, IPAD®, or iPhone®, brand devices available fromApple, Inc. of Cupertino, Calif. or Zune® or Microsoft® Windows devicesavailable from Microsoft of Redmond, Wash. As known in the art, digitalmedia players can serve as both an output device for a computer (e.g.,outputting music from a sound file or pictures from an image file) and astorage device. In one embodiment, device 138 may be computer 102, yetin other embodiments, computer 102 may be entirely distinct from device138. Regardless of whether device 138 is configured to provide certainoutput, it may serve as an input device for receiving sensoryinformation. Devices 138, 140, 142, and/or 144 may include one or moresensors, including but not limited to: an accelerometer, a gyroscope, alocation-determining device (e.g., GPS), light sensor, temperaturesensor (including ambient temperature and/or body temperature), heartrate monitor, image-capturing sensor, moisture sensor and/orcombinations thereof. In certain embodiments, sensors may be passive,such as reflective materials that may be detected by image-capturingdevice 126 and/or sensor 128 (among others). In certain embodiments,sensors 144 may be integrated into apparel, such as athletic clothing.For instance, the user 124 may wear one or more on-body sensors 144 a-b.Sensors 144 may be incorporated into the clothing of user 124 and/orplaced at any desired location of the body of user 124. Sensors 144 maycommunicate (e.g., wirelessly) with computer 102, sensors 128, 138, 140,and 142, and/or camera 126. Examples of interactive gaming apparel aredescribed in U.S. patent application Ser. No. 10/286,396, filed Oct. 30,2002, and published as U.S. Pat. Pub, No. 2004/0087366, the contents ofwhich are incorporated herein by reference in its entirety for any andall non-limiting purposes. In certain embodiments, passive sensingsurfaces may reflect waveforms, such as infrared light, emitted byimage-capturing device 126 and/or sensor 128. In one embodiment, passivesensors located on user's 124 apparel may comprise generally sphericalstructures made of glass or other transparent or translucent surfaceswhich may reflect waveforms. Different classes of apparel may beutilized in which a given class of apparel has specific sensorsconfigured to be located proximate to a specific portion of the user's124 body when properly worn. For example, golf apparel may include oneor more sensors positioned on the apparel in a first configuration andyet soccer apparel may include one or more sensors positioned on apparelin a second configuration.

Devices 138-144, as well as any other electronic device disclosedherein, including any sensory device, may communicate with each other,either directly or through a network, such as network 132. Communicationbetween one or more of devices 138-144 may take place via computer 102.For example, two or more of devices 138-144 may be peripheralsoperatively connected to bus 114 of computer 102. In yet anotherembodiment, a first device, such as device 138 may communicate with afirst computer, such as computer 102 as well as another device, such asdevice 142, however, device 142 may not be configured to connect tocomputer 102 but may communicate with device 138. Further, one or moreelectronic devices may be configured to communicate through multiplecommunication pathways. For example, device 140 may be configured tocommunicate via a first wireless communication protocol with device 138and further communicate through a second wireless communication protocolwith a different device, such as for example, computer 102. Examplewireless protocols are discussed throughout this disclosure and areknown in the art. Those skilled in the art will appreciate that otherconfigurations are possible.

Some implementations of the example embodiments may alternately oradditionally employ computing devices that are intended to be capable ofa wide variety of functions, such as a desktop or laptop personalcomputer. These computing devices may have any combination of peripheraldevices or additional components as desired. Also, the components shownin FIG. 1B may be included in the server 134, other computers,apparatuses, etc.

2. Illustrative Apparel/Accessory Sensors

In certain embodiments, sensory devices 138, 140, 142 and/or 144 may beformed within or otherwise associated with user's 124 clothing oraccessories, including a watch, armband, wristband, necklace, shirt,shoe, or the like. Examples of shoe-mounted and wrist-worn devices(devices 140 and 142, respectively) are described immediately below,however, these are merely example embodiments and this disclosure shouldnot be limited to such.

i. Shoe-Mounted Device

In certain embodiments, sensory device 140 may comprise footwear whichmay include one or more sensors, including but not limited to: anaccelerometer, location-sensing components, such as GPS, and/or a forcesensor system. FIG. 2A illustrates one example embodiment of a sensorsystem 202 in accordance with example embodiments. In certainembodiments, system 202 may include a sensor assembly 204. Assembly 204may comprise one or more sensors, such as for example, an accelerometer,location-determining components, and/or force sensors. In theillustrated embodiment, assembly 204 incorporates a plurality ofsensors, which may include force-sensitive resistor (FSR) sensors 206.In yet other embodiments, other sensor(s) may be utilized. Port 208 maybe positioned within a sole structure 209 of a shoe. Port 208 mayoptionally be provided to be in communication with an electronic module210 (which may be in a housing 211) and a plurality of leads 212connecting the FSR sensors 206 to the port 208. Module 210 may becontained within a well or cavity in a sole structure of a shoe. Theport 208 and the module 210 include complementary interfaces 214, 216for connection and communication.

In certain embodiments, at least one force-sensitive resistor 206 shownin FIG. 2A may contain first and second electrodes or electricalcontacts 218, 220 and a force-sensitive resistive material 222 disposedbetween the electrodes 218, 220 to electrically connect the electrodes218, 220 together. When pressure is applied to the force-sensitivematerial 222, the resistivity and/or conductivity of the force-sensitivematerial 222 changes, which changes the electrical potential between theelectrodes 218, 220. The change in resistance can be detected by thesensor system 202 to detect the force applied on the sensor 216. Theforce-sensitive resistive material 222 may change its resistance underpressure in a variety of ways. For example, the force-sensitive material222 may have an internal resistance that decreases when the material iscompressed, similar to the quantum tunneling composites described ingreater detail below. Further compression of this material may furtherdecrease the resistance, allowing quantitative measurements, as well asbinary (on/off) measurements. In some circumstances, this type offorce-sensitive resistive behavior may be described as “volume-basedresistance,” and materials exhibiting this behavior may be referred toas “smart materials.” As another example, the material 222 may changethe resistance by changing the degree of surface-to-surface contact.This can be achieved in several ways, such as by using microprojectionson the surface that raise the surface resistance in an uncompressedcondition, where the surface resistance decreases when themicroprojections are compressed, or by using a flexible electrode thatcan be deformed to create increased surface-to-surface contact withanother electrode. This surface resistance may be the resistance betweenthe material 222 and the electrodes 218, 220 and/or the surfaceresistance between a conducting layer (e.g., carbon/graphite) and aforce-sensitive layer (e.g., a semiconductor) of a multi-layer material222. The greater the compression, the greater the surface-to-surfacecontact, resulting in lower resistance and enabling quantitativemeasurement. In some circumstances, this type of force-sensitiveresistive behavior may be described as “contact-based resistance.” It isunderstood that the force-sensitive resistive material 222, as definedherein, may be or include a doped or non-doped semiconducting material.

The electrodes 218, 220 of the FSR sensor 206 can be formed of anyconductive material, including metals, carbon/graphite fibers orcomposites, other conductive composites, conductive polymers or polymerscontaining a conductive material, conductive ceramics, dopedsemiconductors, or any other conductive material. The leads 212 can beconnected to the electrodes 218, 220 by any suitable method, includingwelding, soldering, brazing, adhesively joining, fasteners, or any otherintegral or non-integral joining method. Alternately, the electrode 218,220 and associated lead 212 may be formed of a single piece of the samematerial.

Other embodiments of the sensor system 202 may contain a differentquantity and/or configuration of sensors and generally include at leastone sensor. For example, in one embodiment, the system 202 includes amuch larger number of sensors, and in another embodiment, the system 202includes two sensors, one in the heel and one in the forefoot of a shoeor device to be close proximity to a user's foot. In addition, one ormore sensors 206 may communicate with the port 214 in a differentmanner, including any known type of wired or wireless communication,including Bluetooth and near-field communication. A pair of shoes may beprovided with sensor systems 202 in each shoe of the pair, and it isunderstood that the paired sensor systems may operate synergistically ormay operate independently of each other, and that the sensor systems ineach shoe may or may not communicate with each other. It is furtherunderstood that the sensor system 202 may be provided withcomputer-executable instructions stored on one or more computer-readablemedia that when executed by a processor control collection and storageof data (e.g., pressure data from interaction of a user's foot with theground or other contact surface), and that these executable instructionsmay be stored in and/or executed by the sensors 206, any module, and/oran external device, such as device 128, computer 102, server 134 and/ornetwork 132 of FIG. 1A.

ii. Wrist-Worn Device

As shown in FIG. 2B, device 226 (which may resemble or be sensory device142 shown in FIG. 1A) may be configured to be worn by user 124, such asaround a wrist, arm, ankle or the like. Device 226 may monitor athleticmovements of a user, including all-day activity of user 124. In thisregard, device assembly 226 may detect athletic movement during user's124 interactions with computer 102 and/or operate independently ofcomputer 102. For example, in one embodiment, device 226 may be an-allday activity monitor that measures activity regardless of the user'sproximity or interactions with computer 102. Device 226 may communicatedirectly with network 132 and/or other devices, such as devices 138and/or 140. In other embodiments, athletic data obtained from device 226may be utilized in determinations conducted by computer 102, such asdeterminations relating to which exercise programs are presented to user124. In one embodiment, device 226 may also wirelessly interact with amobile device, such as device 138 associated with user 124 or a remotewebsite such as a site dedicated to fitness or health related subjectmatter. At some predetermined time, the user may wish to transfer datafrom the device 226 to another location.

As shown in FIG. 2B, device 226 may include an input mechanism, such asa depressible input button 228 assist in operation of the device 226.The input button 228 may be operably connected to a controller 230and/or any other electronic components, such as one or more of theelements discussed in relation to computer 102 shown in FIG. 1B.Controller 230 may be embedded or otherwise part of housing 232. Housing232 may be formed of one or more materials, including elastomericcomponents and comprise one or more displays, such as display 234. Thedisplay may be considered an illuminable portion of the device 226. Thedisplay 234 may include a series of individual lighting elements orlight members such as LED lights 234 in an exemplary embodiment. The LEDlights may be formed in an array and operably connected to thecontroller 230. Device 226 may include an indicator system 236, whichmay also be considered a portion or component of the overall display234. It is understood that the indicator system 236 can operate andilluminate in conjunction with the display 234 (which may have pixelmember 235) or completely separate from the display 234. The indicatorsystem 236 may also include a plurality of additional lighting elementsor light members 238, which may also take the form of LED lights in anexemplary embodiment. In certain embodiments, indicator system mayprovide a visual indication of goals, such as by illuminating a portionof lighting members 238 to represent accomplishment towards one or moregoals.

A fastening mechanism 240 can be unlatched wherein the device 226 can bepositioned around a wrist of the user 124 and the fastening mechanism240 can be subsequently placed in a latched position. The user can wearthe device 226 at all times if desired. In one embodiment, fasteningmechanism 240 may comprise an interface, including but not limited to aUSB port, for operative interaction with computer 102 and/or devices138, 140.

In certain embodiments, device 226 may comprise a sensor assembly (notshown in FIG. 2B). The sensor assembly may comprise a plurality ofdifferent sensors. In an example embodiment, the sensor assembly maycomprise or permit operative connection to an accelerometer (includingin the form of a multi-axis accelerometer), heart rate sensor,location-determining sensor, such as a GPS sensor, and/or other sensors.Detected movements or parameters from device's 142 sensor(s), mayinclude (or be used to form) a variety of different parameters, metricsor physiological characteristics including but not limited to speed,distance, steps taken, calories, heart rate, sweat detection, effort,oxygen consumed, and/or oxygen kinetics. Such parameters may also beexpressed in terms of activity points or currency earned by the userbased on the activity of the user.

Various examples may be implemented using electronic circuitryconfigured to perform one or more functions. For example, with someembodiments of the invention, a computing device such as a smart phone,mobile device, computer, server, or other computing equipment may beimplemented using one or more application-specific integrated circuits(ASICs). More typically, however, components of various examples of theinvention will be implemented using a programmable computing deviceexecuting firmware or software instructions, or by some combination ofpurpose-specific electronic circuitry and firmware or softwareinstructions executing on a programmable computing device.

II. Monitoring System

FIGS. 3A-B illustrate examples of a computer interacting with at leastone sensor in accordance with example embodiments. In the depictedexample, the computer 102 may be implemented as a smart phone that maybe carried by the user. Example sensors may be worn on a user's body, besituated off-body, and may include any of the sensors discussed aboveincluding an accelerometer, a distributed sensor, a heart rate monitor,a temperature sensor, etc. In FIG. 3, a pod sensor 304 and a distributedsensor 306 (including, for example, sensor system 202 discussed abovehaving one or more FSRs 206) is shown. The pod sensor 304 may include anaccelerometer, a gyroscope, and/or other sensing technology. In someexamples, pod sensor 304 may at least one sensor to monitor data thatdoes not directly relate to user movement. For example, ambient sensorsmay be worn by the user or may be external to the user. Ambient sensorsmay include a temperature sensor, a compass, a barometer, a humiditysensor, or other type of sensor. Other types of sensors and combinationsof sensors configured to measure user movement may also be used. Also,computer 102 may incorporate one or more sensors.

The pod sensor 304, the distributed sensor 206, as well as other typesof sensors, may include a wireless transceiver to communicate with oneanother and the computer 102. For example, sensors 304 and 306 maycommunicate directly with the network 132, with other devices worn bythe user (e.g., a watch, arm band device, etc.), with sensors or devicesworn by a second user, an external device, etc. In an example, a sensorin a left shoe may communicate with a sensor in a right shoe. Also, oneshoe may include multiple sensors that communicate with one anotherand/or with a processor of the shoe. Further, a pair of shoes mayinclude a single processor that collects data from multiple sensorsassociated with the shoes, and a transceiver coupled to the singleprocessor may communicate sensor data to at least one of computer 102,network 132, and server 134. In another example, one or more sensors ofa shoe may communicate to a transceiver that communicates with at leastone of computer 102, network 132, and server 134. Further, sensorsassociated with a first user may communicate with sensors associatedwith a second user. For example, sensors in the first user's shoes maycommunicate with sensors in a second user's shoes. Other topographiesmay also be used.

The computer 102 may exchange data with the sensors, and also maycommunicate data received from the sensors via the network 132 to theserver 134 and/or to another computer 102. A user may wear head phonesor ear buds to receive audio information from the computer 102, directlyfrom one or more of the sensors, from the server 134, from the network132, from other locations, and combinations thereof. The head phones maybe wired or wireless. For example, a distributed sensor 306 maycommunicate data to head phones for audible output to the user.

In an example, a user may wear shoes that are each equipped with anaccelerometer, a force sensor or the like, to allow the computer 102and/or the server 134 to determine the individual movement and metricsof each foot or other body part (e.g., leg, hand, arm, individualfingers or toes, regions of a person's foot or leg, hips, chest,shoulders, head, eyes) alone or in combination with the systemsdescribed above with reference to FIGS. 1A-B and 2A-2B.

Processing of data may distributed in any way, or performed entirely atone shoe, at the computer 102, in the server 134, or combinationsthereof. In the description below, computer 102 may be described asperforming a function. Other devices, including server 134, acontroller, another computer, a processor in a shoe or other article ofclothing, or other device may performing the function instead of or inaddition to computer 102. For example, one or more sensors of each shoe(or other peripheral sensor) could be mated with a respective, localcontroller that performs some or all processing of raw signal output byone or more sensors. The controller's processing, at any given time, maybe subject to command and control of a higher tiered computing device(e.g., computer 102). That higher tiered device may receive and furtherprocess the processed sensor signals, from that one or pluralcontrollers, e.g., via one or more transceivers. Comparisons andcalculations may be made at one or more computing devices, includingsome or all of the above computing devices, with or without additionalcomputing devices. Sensors may sense desired conditions and generate rawsignals, the raw signals being processed so as to provide processeddata. The processed data may then be used for determining currentperformance metrics (e.g., current speed of travel, etc.) and thedeterminations may change depending on user input (e.g., how high did Ijump?) and/or programming (e.g., did the user do the indicated exerciseand, if that is detected, how is it qualified/quantified in the userexperience).

In an example, sensors 304 and 306 may process and store measurementdata, and forward the processed data (e.g., average acceleration,highest speed, total distance, etc.) to the computer 102 and/or theserver 134. The sensors 304 and 306 may also send raw data to thecomputer 102 and/or the server 134 for processing. Raw data, forexample, may include an acceleration signal measured by an accelerometerover time, a pressure signal measured by a pressure sensor over time,etc. Examples of multi-sensor apparel and the use of multiple sensors inathletic activity monitoring are described in U.S. patent applicationSer. No. 12/483,824, entitled “FOOTWEAR HAVING SENSOR SYSTEM,” andpublished as U.S. Publication No. 2010/0063778 A1 and U.S. patentapplication Ser. No. 12/483,828, entitled “FOOTWEAR HAVING SENSORSYSTEM,” and published as U.S. Publication No. 2010/0063779 A1. Thecontent of the above referenced applications are incorporated herein byreference in their entirety. In a particular example, an athlete maywear shoes 302 having one or more force sensing systems, e.g., thatutilize force-sensitive resistor (FSR) sensors, as shown in FIG. 2A anddescribed in the above noted patent publications. The shoe 302 may havemultiple FSR sensors 206 that detect forces at different regions of theuser's foot (e.g., a heel, mid-sole, toes, etc.). Computer 102 mayprocess data from FSR sensors 206 to determine balance of a user's footand/or between a user's two feet. For example, computer 102 may comparea force measurement by a FSR 206 from a left shoe relative to a forcemeasurement by a FSR 206 from a right shoe to determine balance and/orweight distribution.

FIG. 3B is another example data flow diagram in which computer 102interacts with at least one sensor processing system 308 to detect useractions. Sensor processing system 308 may be physically separate anddistinct from computer 102 and may communicate with computer 102 throughwired or wireless communication. Sensor processing system 308 mayinclude sensor 304, as shown, as well as other sensors (e.g., sensor306) instead of or in addition to sensor 304. In the depicted example,sensor system 308 may receive and process data from sensor 304 and FSRsensor 206. Computer 102 may receive input from a user about a type ofactivity session (e.g., cross training, basketball, running, etc.) theuser desires to perform. Instead or additionally, computer 102 maydetect a type of activity the user is performing or receive informationfrom another source about the type of activity being performed.

Based on activity type, computer 102 may identify one or more predefinedaction templates and communicate a subscription to sensor system 308.Action templates may be used to identify motions or actions that a usermay perform while performing the determined type of activity. Forexample, an action may correspond to a group of one or more events, suchas detecting that a user has taken a step to the right followed by astep to the left or detecting that a user has jumped while flicking hisor her wrist. Accordingly, different sets of one or more actiontemplates may be defined for different types of activities. For example,a first set of action templates defined for basketball may includedribbling, shooting a basketball, boxing out, performing a slam dunk,sprinting and the like. A second set of action templates defined forsoccer may include kicking a ball to make a shot, dribbling, stealing,heading the ball and the like. Action templates may correspond to anydesired level of granularity. In some examples, a particular type ofactivity may include 50-60 templates. In other examples, a type ofactivity may correspond to 20-30 templates. Any number of templates maybe defined as needed for a type of activity. In still other examples,the templates may be manually selected by a user rather than beingselected by the system.

Sensor subscriptions may allow sensor system 308 to select the sensorsfrom which data is to be received. The sensor processing system 308 maymanage subscriptions that are used at any particular time. Types ofsubscriptions may include force sensitive resistance data from one ormore force sensitive resistors, acceleration data from one or moreaccelerometers, summation information over multiple sensors (e.g.,summation of acceleration data, summation of force resistance data overone or more sensors, etc.), pressure maps, mean centered data, gravityadjusted sensor data, force sensitive resistance derivatives,acceleration derivatives, and the like and/or combinations thereof. Insome examples, a single subscription may correspond to a summation ofdata from multiple sensors. For example, if a template calls for a shiftin force to the forefoot region of a user's foot, a single subscriptionmay correspond to a summation of forces of all sensors in the forefootregion. Alternatively or additionally, force data for each of theforefoot force sensors may correspond to a distinct subscription.

For example, if sensor system 308 includes 4 force sensitive resistivesensors and an accelerometer, the subscriptions may specify which ofthose 5 sensors are monitored for sensor data. In another example,subscriptions may specify receiving/monitoring sensor data from a rightshoe accelerometer but not a left shoe accelerometer. In yet anotherexample, a subscription may include monitoring data from a wrist-wornsensor but not a heart rate sensor. Subscriptions may also specifysensor thresholds to adjust the sensitivity of a sensor system's eventdetection process. Thus, in some activities, sensor system 308 may beinstructed to detect all force peaks above a first specified threshold.For other activities, sensor system 308 may be instructed to detect allforce peaks above a second specified threshold. Use of different sensorsubscriptions may help a sensor system to conserve power if some sensorreadings are not needed for a particular activity. Accordingly,different activities and activity types may use different sensorsubscriptions.

Sensor processing system 308 may be configured to perform initialprocessing of raw sensor data to detect various granular events.Examples of events may include a foot strike or launch when jumping, amaximum acceleration during a time period, etc. Sensor system 308 maythen pass events to computer 102 for comparison to various templates todetermine whether an action has been performed. For example, sensorsystem 308 may identify one or more events and wirelessly communicateBLUETOOTH® Low Energy (BLE) packets, or other types of data, to computer102. In another example, sensor system 308 may instead or additionallysend raw sensor data.

Subsequent to receipt of the events and/or the raw sensor data, computer102 may perform post-match processing including determining variousactivity metrics such as repetitions, air-time, speed, distance and thelike. Activity classification may be performed by identifying variousevents and actions represented within data received from any number andtype of sensors. Accordingly, activity tracking and monitoring mayinclude determining whether one or more expected or known actions withinan activity type has been performed and metrics associated with thoseactions. In one example, actions may correspond to a series of one ormore low-level or granular events and may be detected using predefinedaction templates.

For example, using action templates, computer 102 may automaticallydetect when a user has performed a particular activity or a particularmotion expected during that activity. If a user is playing basketball,for instance, detecting that the user has jumped while flicking his orher wrist may indicate that the user has taken a shot. In anotherexample, detecting that a user has moved both feet outward while jumpingfollowed by moving both feet inward while jumping may register as a userperforming one repetition of a jumping jack exercise. A variety of othertemplates may be defined as desired to identify particular types ofactivities, actions or movements within types of activities.

FIGS. 4A-B illustrate examples of pod sensors 304 that may be embeddedand removed from a shoe in accordance with example embodiments. The podsensor 304 may include a rechargeable battery that may be recharged wheninserted into a wall adapter 402. Wired or wireless charging of the podsensor 304 may be used. For example, the pod sensor 304 may beinductively charged. In some examples, a pod sensor 304-1 may beconfigured with an interface (e.g., Universal Serial Bus) permittinginsertion into a computer or other device for downloading and/orreceiving data. An interface of the pod sensor may provide for wired orwireless communication. For instance, software updates may be loadedonto the pod sensor when connected to a computer. Also, the pod sensormay wirelessly receive software updates. When physically coupled to acomputer 102 (or other device having a port), the pod sensor may chargeand communicate with the computer 102.

FIG. 5 illustrates example on-body configurations for the computer 102in accordance with example embodiments. Computer 102 may be configuredto be worn at desired locations on a user's body, such as, for example,a user's arm, leg, or chest, or otherwise integrated in clothing. Forexample, each article of clothing may have its own integrated computer.The computer may be a thin client, driven by the context, of what theuser is doing and otherwise equipped/networked. Computer 102 may also belocated apart from the user's body, as shown in FIGS. 6-7.

FIGS. 6-7 illustrates example various off-body configurations for thecomputer 102 in accordance with example embodiments. Computer 102 may beplaced in a docking station 602 to permit display of the GUI on a largerscreen and output of audio through a stereo system. As in otherexamples, computer 102 may respond to voice commands, via direct userinput (e.g., using a keyboard), via input from a remote control, orother manners to receive user commands. Other off-body configurationsmay include placing the computer 102 on a floor or table nearby where auser is exercising, storing the computer 102 in a workout bag or otherstorage container, placing the computer 102 on a tripod mount 702, andplacing the computer 102 on a wall mount 704. Other off-bodyconfigurations may also be used. When worn off-body, a user may wearhead-phone, ear buds, a wrist-worn device, etc. that may provide theuser with real-time updates. The pod sensor 304 and/or the distributedsensor 306 may wirelessly communicate with the computer 102 at theoff-body locations when in range, at periodic time intervals, whentriggered by the user, and/or may store data and upload the data to thecomputer 102 when in range or when instructed by the user at a latertime.

In an example, the user may interact with a graphical user interface(GUI) of the computer 102. FIG. 8 illustrates an example display of aGUI presented by a display screen of the computer 102 in accordance withexample embodiments. Home page display 802 of the GUI may present a homepage to provide the user with general information, to prompt the user toselect what type of physical activity session the user is interested inperforming, and to permit the user to retrieve information aboutpreviously completed sessions (e.g., basketball games, workouts, etc.).The display screen of the computer 102 may be touch sensitive and/or mayreceive user input through a keyboard or other input means. Forinstance, the user may tap a display screen or provide other input tocause the computer 102 to perform operations.

To obtain information about a previous session, the user may tap orotherwise select on a field 804 including the last session to cause thecomputer 102 to update the home page display 802 to display performancemetrics (e.g., vertical leap, total air, activity points, etc.) from atleast one previous session. For example, the selected field 804 mayexpand, as seen in FIG. 8, to display information about duration of thelast session, the user's top vertical leap, a total amount of time auser was in the air during the last session, and incentive points (e.g.,activity points) earned in the previous session. The computer 102 maydetermine performance metrics (e.g., speed, vertical leap, etc.) byprocessing data sensed by the sensors 304 and 306 or other sensingdevices.

Home page display 802 may prompt a user to select whether they wish tohave the computer 102 track one or more user performance metrics duringa workout or athletic activity session (e.g., track my game) byselecting field 806 or assist the user in improving their athleticskills (e.g., raise my game) by selecting field 808. FIGS. 9-21 discussthe former and FIGS. 22-31 discuss the latter.

FIG. 9 illustrates example performance metrics for user selection inaccordance with example embodiments. In an example, a user may beinterested in monitoring their total play time, vertical leap, distance,and calories burned and/or other metrics, and may use the home pagedisplay 802 to select from the desired metrics shown in FIG. 9. Themetrics may also vary based on type of athletic activity performed in asession. For example, home page display 802 may present certain defaultperformance metric selections, depending on the activity of the session.The user may provide input to change the default performance metricselections.

Other performance metrics than the ones shown in FIG. 9 may include atotal number of jumps, a number of vertical jumps above a certain height(e.g., above 3 inches), a number of sprints (e.g., speed above a certainrate, either user selected or specified by computer 102), a number offakes (e.g., quick changes in direction), a jump recovery (e.g., afastest time between two jumps), a work rate (e.g., may be a function ofaverage power multiplied by time length of workout session), a work ratelevel (e.g., low, medium, high), total steps, steps per unit time (e.g.,per minute), number of bursts (e.g., number of times a user exceeds aspeed threshold), balance, weight distribution (e.g., compare weightmeasured by a FSR 206 in a user's left shoe to weight measured by a FSR206 in a user's right shoe, as well as amount FRSs 206 in one shoe),average time duration of sessions, total session time, average number ofrepetitions per exercise, average number of points earned per session,total number of points, number of calories burned, or other performancemetrics. Additional performance metrics may also be used.

In an example, computer 102 may prompt the use to indicate which metricsto monitor for each type of session (e.g., baseball, soccer, basketball,etc.) and store the identified metrics in a user profile. Computer 102may also prompt the user for desired metrics at the beginning of eachsession. Further, computer 102 may track all of the performance metrics,but may only display the selected metrics to the user in the GUI. Forexample, computer 102 may only monitor certain base metrics (e.g., basedon battery life may be extended, to vary responsiveness, to avoid dataoverload, etc.). If the user desires to review metrics other than theones currently displayed by the GUI, the user may input the desiredmetrics and the computer 102 may update the GUI accordingly. The metricsbeing displayed may be changed at any time. The default metrics may bepresented once the session resumes or another session begins.

If computer 102 monitors more metrics than can be displayed, computer102 may later go into a lower level of monitoring (e.g., as resourcesare consumed together with warnings to user), down to and through baseand ultimately to one or no metrics being monitored. In an example,computer 102 may only display base metrics for a user, unless/untilconfigured otherwise by user. Based on resources, computer 102 mayreduce what is being displayed to only present the base performancemetrics or fewer metrics. Sensors may continue to monitor the otherperformance metrics, and data from these sensors may be later available(e.g., via web experience, etc.).

At the beginning of a session, computer 102 may calibrate the sensors ofthe shoes. FIGS. 10A-C and 11A-B illustrate an example of calibratingsensors in accordance with example embodiments. Calibration may involvecomputer 102 confirming ability to communicate directly or indirectlywith the sensors (e.g., sensors 304 and 306), that the sensors arefunctioning properly, that the sensors have adequate battery life, andto establish baseline data. For example, computer 102 may communicatewith (e.g., send a wireless signal) pod sensor 304 and distributedsensor 306 contained with a user's shoes. The pod sensor and thedistributed sensor may reply with the requested data. Calibration mayalso occur at other time instances (e.g., mid-session, at the end of asession, etc.).

During calibration, the GUI may prompt the user to stand still to takebaseline data measurements with pod sensor 304 and distributed sensor306 (e.g., acceleration, weight distribution, total weight, etc.), asseen in displays 1002A-B. Calibration may also prompt the user toindividually lift their feet to permit computer 102 to determine whichfoot is associated with which sensor data. Distributed sensor 306 mayalso be encoded with footwear information, such as, for example, shoetype, color, size, which foot (e.g., left or right), etc., that thecomputer 102 obtains during calibration. The computer 102 (or server134) may process the reply from the sensors 304 and 306, and update theGUI to inform the user of any issues and how to address those issues(e.g., change battery, etc.) or if the calibration was successful, asseen in display 1002C. In FIG. 11A, for instance, field 1104 shown tothe left of display 1102A includes example displays of battery life aswell as connectivity status (e.g., connected, not connected).Calibration may also occur at certain events, such as detecting removalof a pod 304. Based on the calibration, the display 1102B, as shown inFIG. 11B, presents a weight distribution for the user and a gauge 1106representing remaining battery life. Either as part of calibrating oneor more sensors and/or as a separate feature or function, a GUI may beconfigured to display performance data in substantially real-time (e.g.,as fast as may be permitted to capture (and/or process) and transmit thedata for display). FIGS. 11C-D show example GUIs that may be implementedin accordance with one embodiment. As seen in FIG. 11C, display 1102Cmay provide one or more selectable activity parameters for displayingcaptured values relating to that selectable parameter. For example, auser desiring to view values relating to their vertical height during ajump may select the “vertical” icon (see icon 1108); yet other icons mayinclude, but are not limited to: quickness (which may display valuesrelating to steps per second and/or distance per second), pressure,and/or any other detectable parameter. In other embodiments, a pluralityof different parameters may be selected for simultaneous display. Yet infurther embodiments, the parameters are not required to be selected.Default parameters may be displayed absent a user input. Data relatingto the parameter(s) may be provided on display 1102C in real-time. Forexample, output 1110 indicates that the user has jumped “24.6 INCHES”.Values may be provided graphically, such as for example represented bygraph 112 indicating the value is 24.6 inches. In certain embodiments,outputting of values, such as through outputs 1110 and/or 1112, may showthe real-time data, in yet other embodiments, at least one of theoutputs 1110/1112 may show other values, such as historical values,desired goal values, and/or a maximum or minimum value. For example,graph 1112 may fluctuate depending on the user's current (e.g.,real-time) height; however, output 1110 may display the user's highestrecorded jump during that session or an all-time best. Outputting ofvalues or results may be correlated to physical objects and/or actions.For example, upon a user jumping a vertical height within a first range,such as between 24 inches to 30 inches, they may receive an indicationthat they could jump over a bicycle (see, e.g., display 1102D of FIG.11D). As another example, values relating to a user's quantity of stepsper second may be correlated to those of actual animals and displayed.Those skilled in the art will appreciate that other physical objects maybe utilized in accordance with different embodiments.

Computer 102 may prompt the user to start a session. FIGS. 12A-Dillustrate example displays of the GUI presenting information relativeto a session in accordance with example embodiments. Display 1202A mayinitially prompt the user to check in to a court and to start a session.The user may also input a type of the session (e.g., practice, pickupgame, league, half-court game, full court game, 3 on 3, 5 on 5, etc.).Display 1202B may inform the user of a duration of the session as wellas prompting the user to pause and/or end their session. Display 1202Cmay present current performance metrics of the user (e.g., top vertical,air time, tempo, etc.). For viewing purposes, display 1202 may presentdefault or user-selected statistics, but a swipe or other gesture maytrigger a scroll, sequencing groups of predetermined number ofperformance metrics (e.g., 3 or other number, based on the performancemetrics that can be shown on the screen in portrait versus landscapeorientation) or otherwise brings up other performance metrics.

Computer 102 may also update display 1202 when a particular event isidentified. For example, if a new record (e.g., personal best) isidentified (e.g., new vertical max leap), computer 1202 may at least oneof update the display (e.g., color, information presented, etc.),vibrate, sound a noise indicative of the specific record (e.g., based oncolor change placement on shoe corresponding to a specific metric), orprompt the user that some record (e.g., any metric) has been reached.Display 1202 may also present a button for the user to select signifyingthat a record has been achieved. Display 1202B may prompt the user tocheck their performance metrics (e.g., check my stats), as furtherdescribed in FIG. 13.

FIG. 13 illustrates an example display of a GUI providing a user withinformation about their performance metrics during a session inaccordance with example embodiments. Display 1302 may presentinformation about a length of a current or previous session in field1304, various performance metrics (e.g., top vertical, total airtime,tempo, etc.) for the user in field 1308, as well as who the user playedwith during the session in field 1310. For example, computer 102, sensor304 or 306, or other device associated with a first user may exchange afirst user identifier with a computer 102, sensor 304 or 306, or otherdevice associated with a second user to that each computer may be awareof who participated in a session.

The computer 102 may also process the performance metrics to assign aplaying style to the user as indicated in field 1306. Field 1306 mayindicate that the user is a “hot streak” in response to determining thatthe user hustled hard for thirty minutes in a row. The box to the rightof field 1306 may indicate alternative playing styles. The computer 102may identify other types of playing styles. For example, the computer102 may assign a ‘silent assassin’ playing style when identifyingperiods of inactivity followed by explosive bursts, a ‘vortex’ playingstyle when a user exhibits little movement or jumping during thesession, a ‘cobra’ playing style when a user exhibits perpetual easymovement with huge bursts and jumps, a ‘track star’ playing style when auser is fast, has good stamina, and has a high peak speed, and a‘skywalker’ playing style when a user has a big vertical leap and a longhang time. In some examples, more than one style may be assigned to theuser, with a different style associated with one individual session ascompared with another session. Plural styles may be assigned anddisplayed for a single session.

The computer 102 may assign a particular playing style based onreceiving user data from at least one of pod sensor 304 (e.g.,accelerometer data), distributed sensor 306 (e.g., force data), or othersensors. The computer 102 may compare the user data with playing styledata for a plurality of different playing styles to determine which ofthe playing styles most closely matches the data. For example, thecomputer 102 may set performance metric thresholds for each of theplaying styles. Some playing styles may require that, at least onceduring the session, the user jumped a certain height, ran at a certainspeed, played for a certain amount of time, and/or performed othertasks. Other playing styles may require that the user data indicate thatthe user performed certain sequences of events (e.g., little movementfollowed by quick acceleration to at least a certain top speed). Someplaying styles may require that the user data indicate that the usermaintained thresholds for a certain amount of time (e.g., maintainedaverage speed over a threshold throughout a game).

In an example, a playing style may be assigned based on a data setobtained from a set of sensors including sensors worn at variouslocations on a user's body (e.g., accelerometers at the gluteus and orupper body to identify a “BANGER” playing style). Also, other,non-activity data may come into determining a playing style, such asuser profile data (e.g., user age, height, gender, etc.). For example,some playing styles may be gender specific or based on ambientconditions (e.g., a “POSTMAN” style because use plays in rain, sleet,snow, etc.).

A user or user group may define their own playing styles, based on acombination of metrics and analytics. The users or user groups maychange a name of the playing style, without changing the associatedmetrics and analytics. Playing styles may be updated automatically. Forexample, personal training system 100 may periodically update a playingstyle specified by system 100. In another example, system 100 mayautomatically update a playing style when the name of the playing styleis associated with a particular location (e.g., state, city, court), andthat playing style is referred to by a different name at anotherlocation (e.g., keep the designation consistent with local lingo).

In FIG. 13, display 1302 permits the user to share their performancemetrics with other users and/or to post to a social networking websiteby selecting field 1312. The user may also input a message (e.g., “checkout my vertical leap”) to accompany the performance metrics being sent.The computer 102 may distribute performance metric data of a currentand/or previous session and the message to the server 134 in response toa user request to share. The server 134 may incorporate the data and/ormessage in the social networking website and/or may distribute thedata/message to other desired or all users.

FIG. 14A-C illustrates example displays of the GUI presentinginformation about a user's virtual card (vcard) in accordance withexample embodiments. The vcard may include information about a user'sathletic history. The vcard may include data on a user's performancemetrics, sessions, and awards at individual sessions as well as averagesof the performance metrics. The vcard statistics display 1402A mayindicate a number of points a user has acquired (e.g., activity pointsor metrics), as well as running totals and/or top performances by theuser. The activity points may a statistic indicating physical activityperformed by a user. The server 134 and/or computer 102 may awardactivity points to the user upon achieving certain athletic milestones.The vcard sessions display 1402B may indicate a total amount of playtimeand number of sessions a user has completed, as well as providinghistorical information about completed sessions. The vcard sessionsdisplay 1402B may also indicate a playing style the user exhibited foreach session as well as a session length and date of the session. Thevcard awards display 1402C may indicate awards the user has accrued overtime. For example, the server 134 and/or computer 102 may award the usera flight club award after accruing a total amount of loft time duringthe sessions.

Other example awards may be a “king of the court” award for a user whohas one or more top metrics at a specific court, a “flier mile” awardearned with one mile of flight time (or for other quanta of time anddistance), a “worldwide wes” award when a player participates insessions in multiple countries, an “ankle-breaker” award to those havingat least a certain top speed or quickest first step, a “jump king” awardfor a user having at least a certain vertical leap, a “24/7 baller”award for a user who plays a certain number of days in a row or at acertain number of different courts, an “ice man” award if a certainnumber of rivals follow a user, a “black mamba” award if an even greaternumber of rivals follow a user (compared to an ice-man), a “prodigy”award for a young player achieving certain performance metric levels,and an “old school” award for older players achieving certainperformance metric levels. Other types of awards may also be awarded.

FIG. 15 illustrates an example user profile display of the GUIpresenting a user profile in accordance with example embodiments. Theuser profile display 1502 may present information about the user, suchas height, weight, and position, playing style (e.g., “The SilentAssassin”), as well as other information. The user profile display 1502may also indicate one or more types of shoe worn by the user. The userprofile display 1502 may present information about the user's activity,and may permit the user to control sharing this information with otherusers. For example, the user may specify which other users can view userprofile information, or may make all of the user's informationaccessible to any other user. FIG. 16 illustrates further examples ofinformation about the user that may be presented in user profile display1502 in accordance with example embodiments.

FIGS. 17A-D, 18A-C, 19A-D and 20A-B illustrate further example displaysof a GUI for displaying performance metrics to a user in accordance withexample embodiments. During, at the end of a session, or both, thecomputer 102 may communicate with at least one of pod sensor 304,distributed sensor 306, or other sensor, to obtain data to generate theperformance metrics. Example displays of the GUI while capturing dataare shown in FIGS. 17A-D, such as top vertical in display 1702A, totalairtime in display 1702B, tempo statistics in display 1702C, and pointsin display 1702D. Scroll bar 1704 represents the progress intransferring data from the sensors to computer 102.

FIGS. 18A-B illustrate example leap displays relating to a user'svertical leap in accordance with example embodiments. The computer 102may track information on the user's vertical leap during an exercisesession as well as at what times during the session the leaps occurred.The computer 102 may determine a user's vertical leap based on an amountof loft time between when both feet of a user leave the ground and whena first of the user's feet next contacts the ground. The computer 102may process accelerometer data from pod sensor 304 and/or force datafrom distributed sensor 306 to determine a moment when both of theuser's feet are off the ground and when a first of the feet nextcontacts the ground. The computer 102 may also compare user data frompod sensor 304 and distributed sensor 306 with jump data to confirm thatthe user actually jumped and landed, rather than merely lifted theirfeet off of the ground or hung on a basketball rim (or other object) fora predetermined time. The jump data may be data generated to indicatewhat a force profile and/or acceleration profile should look like forsomeone who actually jumped. The computer 102 may use a similaritymetric when comparing the user data to the jump data. If the user datais not sufficiently similar to the jump data, the computer 102 maydetermine that the user data is not a jump and may not include the userdata when determining a user's performance metrics (e.g., top or averagevertical leap).

Provided that the computer 102 determines that the user data is for ajump, the computer 102 may process the user data to determine a verticalleap, a time of the vertical leap, a user's average vertical leapheight, maintain a running total of loft time for jumps, and/ordetermine which foot is dominant, as well as other metrics. The computer102 may identify a dominant foot based on the force data and/oraccelerometer data associated with each shoe. The force data and/oraccelerometer data may include timing information so that the computer102 can compare events in each shoe. The computer 102 may process theforce data and/or accelerometer data as well as the timing informationto determine which foot was last on the ground prior to a jump. Thecomputer 102 may identify a dominant foot based on the one that is laston the ground when a user jumps and/or the one associated with a user'slargest vertical leap. The computer 102 may also present leap display1802A including a user's top five vertical leaps and depict which foot,or both feet, was last on the ground immediately preceding the jump.Leap display 1802A may display any desired number of top leaps, whichmay be specified by the user or set by system 100. The number of topleaps may be based on an amount of time. For example, leap display 1802Amay present the top five leaps over the full time of a session, top fivein the most recent predetermined number of minutes or percentage oftotal session time, or based on the type of session (e.g., pick-upbasketball game as compared to an organized game). The leap display1802A or 1802B may also display vertical leaps over durations other thanby session, and may include, for example, month, week, all time, orother time ranges. Leap display 1802A or 1802B may also present a totalnumber of jumps, a cumulative amount of hang time, an average hang time,hang time corresponding to a highest vertical leap, or other informationrelating to jumping. Orientation of computer 102 may control which ofleap display 1802A and leap display 1802B is currently being presented.For example, a user may rotate computer 102 (e.g., 90 degrees) to changefrom presenting leap display 1802A (e.g., a portrait orientation) topresenting leap display 1802B (e.g., a landscape orientation). A usermay rotate computer 102 in the opposite direction to change frompresenting leap display 1802B to presenting leap display 1802A.Similarly, rotation of computer 102 may be used to alternate betweendisplays in other examples described herein.

In another example, leap display 1802B may display a user's jumpschronologically over a session and may indicate a time when each jumpoccurred as well as vertical height for each jump during the session.The leap display 1802B may also display a user's personal best verticalleap from a previous session or previously set during the session. In anexample, a personal best line can be changed during a session, eithervia a step function, or by adding a new line of the new best tosupplement the existing line (e.g., “new best” color) and showing linesfor the session in which the new best occurs. Computer 102 may alsoupdate leap display 1802B by replacing the previous personal best line(e.g., in one color) with a new line (e.g., in a new personal bestcolor, which may only be used during the session in which the personalbest occurred). Further, the color may change as the user's personalbest improves to indicate ability compared to other users (e.g., youjumped higher than 85% of other users).

The leap display 1802B may include a performance zone (e.g., dunk zone)indicating when a user may be able to perform an act (e.g., dunk abasketball). The computer 102 may tailor the performance zone to theuser based on the user's physical attributes (e.g., height, arm length,leg length, torso length, body length, etc.). For example, a dunk zonemay require a higher vertical leap for a shorter user than a talleruser.

A performance zone may correspond to a range of values, a minimum value,or a maximum value. The one or more values may correlate to when auser's athletic performance is expected that a user could perform aparticular act. For example, a performance zone may be a minimumvertical leap that would permit a user to dunk a basketball. The userneed not actually perform the act (e.g., dunking), but instead theperformance zone may indicate when the computer 102 calculates that theuser could perform the act.

Based on sensor data obtained from one or more sessions, computer 102may provide a recommendation to help the user achieve the performancezone. For example, computer 102 analysis of sensor data associated withleaps by the user may enable more feedback to the user to enhanceability to get into the dunk zone or to improve personal bests in rareair. For instance, computer 102 may process sensor data and recommendthat the user adjust certain body parts to increase the user's leapingability. In another example, computer 102 may suggest that the userobtain greater acceleration of leading foot or more pressure on trailingfoot by increasing upper body acceleration.

A performance zone may be established for any desired athletic movement.Example performance zones may correspond to a minimum amount of pressuremeasured by distributed sensor 306, a maximum amount of pressure,pressure falling within a particular range or pressures. Other exampleperformance zones may correspond to a minimum amount of accelerationmeasured by the sensor 306, a maximum amount of pressure, pressurefalling within a particular range or pressures. Also, a performance zonemay be based on a combination of different measurements or a sequence ofmeasurements. For example, a performance zone may specify at least acertain amount of acceleration, followed by at least a certain amount ofloft time, followed by at least a certain amount of measured pressure.

In gymnastics, for example, acceleration and body rotation may bemonitored. For instance, it may be desirable for a gymnast to have aspecific amount of body rotation during a dismount from the uneven bars.If the gymnast rotates too quickly or slowly, he or she may not orienttheir body in a proper position when landing. The performance zone maybe a “spin zone” specifying minimum and maximum rotationalaccelerations, and computer 102 may monitor for over and under rotationto provide the gymnast with feedback on whether they are within aperformance zone during a dismount. Computer 102 may provide arecommendation to adjust certain body parts to adjust an amount ofacceleration when dismounting to increase or decrease rotation by theuser. A performance zone may be established for other sports (e.g.,track and field, golf, etc.).

Computer 102 may tailor the performance zone based on feedback receivedform the user. In an example, computer 102 may receive input from a userindicating for which vertical leaps the user was able to perform the act(e.g., dunk a basketball), and the computer 102 may adjust a minimumrequired vertical leap for the user to be in the performance zone basedon the user's feedback. Computer 102 may award one or more activitypoints to a user for being in the performance zone as well as for theamount of time the user maintained their performance within theperformance zone. Computer 102 may also determine an amount of caloriesburned by the user while in the performance zone.

Computer 102 may present information indicating a rate of activitypoints earned by a user over the duration of an exercise session. FIG.18C illustrates an example activity points display 1804 in accordancewith example embodiments. Computer 102 may determine and award activitypoints to a user during the exercise session. To do so, computer 102 maycompare measured user performance to any number of metrics to awardactivity points. For example, computer 102 may award a predeterminednumber of activity point for running a predetermined distance. As may beseen in FIG. 18C, line 1806 of activity points display 1804 mayrepresent the rate at which a user earned activity points at varioustimes during the exercise session, line 1806 may represent an all-timeaverage rate at which a user has accrued activity points, line 1808 mayrepresent the average rate at which the user accrued activity pointsduring this particular session, and line 1812 may represent an all-timebest rate for accruing activity points. In an example, line 1806 mayrepresent how may activity points a user accrues per minute, or otherinterval of time (e.g., per millisecond, per second, per ten seconds,per thirty seconds, etc.). Activity points display 1804 may also presentindicia, such as lines, indicating other matrices, such as averages,including but not limited to an average rate of accrued activity pointsfor a predetermined number of previous session (e.g., last threesessions). Further, the lines may be of different colors. If a newall-time best is established, activity points display 1804 may flash orotherwise present an indication signifying the accomplishment.

Computer 102 may categorize activities performed by the user as well asa percentage of time during an exercise session a user was in aparticular category, and present this information to the user in theactivity points display 1804. For example, activity points display 1804may indicate a percentage of time during a session that a user was idle,percentage of time that the user moved laterally, percentage of timethat the user was walking, percentage of time that the user was running,percentage of time that the user was sprinting, and percentage of timethat the user was jumping, etc. Other categories instead of or inaddition to the ones shown in activity points display 1804 may also bepresented. Further, activity points display 1804 may display acumulative amount of time, rather than percentage of time, for each ofthese statistics. Computer 102 may determine that amount of activitypoints a user earned while in each category, as well as a total amountof activity points earned during an exercise session, and present suchinformation via activity points display 1804. In an example, computer102 may determine that a user earned 25 activity points while walking,75 activity points while walking, and 150 activity points whilesprinting, for a total of 250 activity points. Computer 102 may alsodetermine a caloric burn rate for each of the categories instead of orin addition to determining activity points.

The computer 102 may also display performance metric data based onmeasurements of a user's hustle and tempo. FIGS. 19A-D illustrateexample hustle displays 1902A-B and tempo displays 1904A-B in accordancewith example embodiments. Hustle display 1902A may present a user'shustle over time during a session, as well as other performance metrics.For example, computer 102 may track various performance metricsincluding a running total of jumps, sprints, fakes, and jump recovery(e.g., a shortest amount of time between consecutive jumps) during asession, and hustle may be a function of these metrics. With referenceto hustle display 1902B, computer 102 may divide hustle into threecategories: low, medium and high. More or fewer categories of hustle maybe defined. Hustle display 1902B may also present line 1906 indicatingan average hustle level over a session.

With reference to tempo display 1904A, computer 102 may presentinformation on a user's tempo during a session. Tempo may be based on arate of steps taken by a user per interval of time (e.g., steps perminute). The categories may be defined by ranges of step rates. Forexample, walking may be defined as one to 30 steps per minute, joggingmay be 31-50 steps per minute, running may be defined as 51-70 steps perminute, and sprinting may be defined as 71 or more steps per minute.With reference to tempo display 1904B, computer 102 may indicate howoften a user was in each category during a session. For example, tempodisplay 1904B may indicate what percentage of the time a user was ineach category (e.g., 12% sprinting). Tempo display 1904 may alsoindicate a user's quickest number of steps per second (e.g., 4.1steps/second) or any other time interval, a total number of steps, atotal number of sprints, etc.

The computer 102 may also inform the user of activity points earnedduring the workout as well as total activity points accrued. FIGS. 20A-Billustrate example activity points displays of a GUI informing a user ofpoints earned during a session in accordance with example embodiments.The computer 102 may process data taken during a workout session toaward points to a user. The points may track a user's activity acrossdifferent sports and workout sessions. The points display 2002A-B maypermit the user to determine points earned by date range, workoutsession, or other ranges.

The computer 102 may also track user defined movement. FIGS. 21A-Cillustrate example freestyle displays of a GUI providing information onfreestyle user movement in accordance with example embodiments. Infreestyle display 2102A, computer 102 may prompt the user to start amovement for tracking. The user may perform any desired type ofmovement, denoted hereafter as “freestyle” movement. In freestyledisplay 2102B, computer 102 may display a user's vertical leap, airtime,and foot used for a jump during the freestyle movement. Freestyledisplay 2102B may display performance metrics deemed relevant by thesystem 100, by the user, or both. For example, performance metrics couldbe the vertical leap, airtime, foot, as shown in display 2102B, could bethe weight distribution shown in display 2102C, or both with the usercycling through. In freestyle display 2102C, computer 102 may display aweight distribution measured by distributed sensor 306. The user mayalso review weight distributions over time to determine how the user'sweight distribution may have affected a user's availability to move orleap. A user may, for example, slide their finger across display to movebetween displays 2102A-C.

In addition to monitoring a user's performance during a session,computer 102 may assist a user in improving their athletic skills. FIGS.22A-B illustrate example training displays 2202A-B presentinguser-selectable training sessions in accordance with exampleembodiments. The training sessions may guide the user through a set ofmovements designed to improve a user's athletic ability. Exampletraining sessions may include a shooting practice, an all around theworld game, a buzzer beater game, a pro-player game, a basic game, anair time game, a continuous crossover game, a free throw balance game, asignature moves game, a pro battles game, and a horse game. Thesetraining sessions are further described in FIGS. 23-26. For example,computer 102 may have a touchscreen permitting a user to scroll betweenand select the training sessions shown in FIGS. 23-26.

FIGS. 27, 28A-C, 29A-B, and 30A-C illustrate display screens for GUIsfor a basketball shooting training session in accordance with exampleembodiments. In FIG. 27, training display 2702 may present the user withinformation on their last session (e.g., shooting percentage for freethrows, three pointers, and jump shots) and prompt the user to begin anew session. The computer 102 may monitor touches on a pressuresensitive display screen to track makes and misses. To do so, thecomputer 102 may monitor how many fingers were used to distinguishbetween basketball shots. For example, three fingers may be used toindicate a three point shot in basketball, two fingers may be used toindicate a two point shot, and a single finger may be used to indicate afree throw, as seen in FIGS. 28A-C. A tap of one or more fingers on thedisplay screen may indicate a made shot, and a swipe of one or morefingers across a portion of the display screen may indicate a miss. Inother examples, a down swipe across a display screen of computer 102with one or more fingers may indicate a make and an up swipe with one ormore fingers may indicate a miss.

The computer 102 may process the user input to determine a number offingers used as well as between a tap and a swipe. The computer 102 maydetermine an amount of area of the display screen covered by the fingerswhen tapping and/or swiping the display screen to distinguish betweenone, two, or three fingers. The computer 102 may also determine durationof the touch and if a region of the display screen initially contactedby the user differs from a region of the display screen at the end ofthe touch to distinguish between a tap and a swipe. At the end of asession, the training display 2702 may display information on makes andmisses to the user, as seen in FIGS. 29A-B. The training display 2702may display makes/misses by shot type as well as totals for all shottypes. For example, training display 2702A may display makes and missesfor free throws, and training display 2702B may display makes and missesfor jump shots. Training display 2702B may aggregate 2 and 3 pointbasketball shots and may display makes and misses together, or separatedisplays may present makes and misses for each type of shot.

FIGS. 30A-C illustrate example displays for a GUI providing the userwith information on a shooting practice session in accordance withexample embodiments. Shot summary display 3002A may permit the user toselect all shots or a particular shot type to receive information onpercentage of shots made (e.g., 55.6%), a streak of how many shots weremade consecutively, and the user's vertical leap “sweet spot” for themakes. The sweet spot may indicate a vertical leap where a user'sshooting percentage (e.g., percentage of made shots) exceeds apredetermined amount (e.g., 50%). The computer 102 may process data fromthe pod sensor 304 and/or from distributed sensor 306 to provide theuser information about their makes and misses via the GUI. Thisinformation may include on average vertical leap for makes and misses toinform the user about how jump height affects their shootingperformance. Shot summary display 3002B may inform the user which footwas used when jumping as part of a shot along with a height of avertical leap, and whether a shot was made or missed. Shot summarydisplay 3002C may provide the user with information about three pointshots made and missed.

The shot summary display 3002 may provide the user with statisticinformation as to how their balance affects their shots by indicatinghow many balanced shots were made and how many off-balanced shots weremade. The computer 102 may determine balance based on weightdistribution measured by distributed sensor 306 while a user took ashot. If weight is relatively evenly distributed between a user's twofeet (i.e., within a certain threshold), the computer 102 may identify ashot as being balanced. When weight is not relatively evenly distributedbetween a user's two feet (i.e., outside of a certain threshold), thecomputer 102 may identify a shot as being unbalanced. The shot summarydisplay 3002C may also provide a user with feedback about their balanceand tips to correct any issues with unbalanced weight distribution. Forexample, field 3004 may indicate how many shots were made when a user'sweight was balanced and field 3006 may indicate how many shots were madewhen a user's weight was off-balance.

In an example, computer 102 may receive and process data generated by aforce sensor to determine a weight distribution during a performance ofan exercise task (e.g., shooting a jump shot in basketball). Computer102 may process user input indicating successful completion of anexercise task (e.g., a make). Computer 102 may associate a detectedweight distribution at a time preceding the user input indicatingsuccessful completion of the exercise task. For example, computer 102may process sensor data to identify movement consistent with abasketball shot, and determine a weight distribution starting withdetecting lift-off when a user jumps during a jump shot, a period oftime prior to lift-off, landing, and a period of time after landing.Computer 102 may monitor weight distribution for these periods of time.At a subsequent time (e.g., second or subsequent jump shot), computer102 may process additional user input indicating unsuccessful completionof the exercise task (e.g., a miss). Computer 102 may associate adetected weight distribution at a time preceding the user input with theunsuccessful completion of the exercise task. After or during theexercise session, computer 102 may present to the user information abouttheir weight distribution and about how the distribution has affectedthe user's ability to complete the exercise task.

The GUI may also provide the user with incentives to working on theirbasketball shot. FIG. 31 illustrates an example display of a GUIinforming the user of shooting milestones in accordance with exampleembodiments. Milestone display 3102 may inform the user of one or moreshot thresholds and how many shots a user has made. For example,milestone display 3102 may indicate that a user has made 108 shots, suchthat the user has reached amateur status, and needs to make anadditional 392 shots to achieve the next status level.

As a part of drills for enhancing a user's skills, computer 102 mayprompt the user to perform moves similar to the ones used byprofessional athletes. FIGS. 32A-C illustrate example signature movesdisplays for a GUI prompting a user to perform a drill to imitate aprofessional athlete's signature move in accordance with exampleembodiments. In addition to professional athlete signature moves, usersmay create and share signatures moves with other users.

In an example, a user may input a search query into signature movesdisplay 3202A to initiate a search for a desired professional athlete.The computer 102 may forward the search query to the server 134, whichmay reply with query results. The server 134 may also provide thecomputer 102 with suggested signature moves for display prior to a userinputting a search query. As seen in signature moves display 3202A,computer 102 may display different signature moves for user selection.Upon selection of a particular move, signature moves display 3202B maypresent video of the signature move and provide the professional'sperformance metrics for the move. The computer 102 may, for instance,query the server 134 for signature move data in response to the user'sselection to generate signature moves display 3202B. The signature movedata may include data from pod sensor 304 and distributed sensor 306 ofa professional athlete performing a signature move. The user may attemptto imitate the signature move and the computer 102 may process the userdata to indicate the accuracy of the imitation.

After completion of an attempt of the signature move, the computer 102may inform the user how well they successfully imitated the move. Toidentify a match, the computer 102 may compare data obtained from podsensor 304 and/or distributed sensor 306 with the signature move data todetermine if the two are similar. The computer 102 may monitor how longa user took to complete the signature move, a vertical leap of the user,airtime of the user, tempo of the user, or other information and comparethis data to corresponding data from the professional athlete. Thecomputer 102 may also indicate how accurately the user imitated thesignature move of the professional athlete, as shown in signature movesdisplay 3202C. Accuracy may be based on a combination of how similareach of the performance metrics is to the professional's. The computer102 may weight certain metrics more highly than others, or may weighteach metric equally. For example, the signature move data may provideinformation on three different metrics, and may compare the user's datato each of the three metrics. The computer 102 may determine a ratio ofthe user's performance metric to the professional's metric and mayidentify a match if the ratio is above a threshold (e.g., more than80%). Accuracy also may be determined in other manners.

In an example, computer 102 may receive signature move datacorresponding to acceleration and force measurement data measured by afirst user (e.g., a professional athlete) performing a sequence ofexercise tasks (e.g., cuts in basketball followed by a dunk). Computer102 may receive and process user data generated by at least one ofsensors 304 and 306 by monitoring a second user attempting to performthe same sequence of exercise tasks. Computer 102 may then generate asimilarity metric indicating how similar the user data is to thesignature move data.

Computer 102 may also provide the user with data on performance metricsfrom other users and/or professional athletes for comparison as part ofa social network. FIGS. 33A-C illustrates example displays of a GUI forsearching for other users and/or professional athletes for comparison ofperformance metrics in accordance with example embodiments. Computer 102may communicate with the server 134 to identify professional athletes orfriends of the user, as seen in display 3302A. Each individual may beassociated with a unique identifier. For example, the user may select toadd a friend or a professional, as seen in the GUI display on the left.When a user elects to add a friend/professional, the user may input asearch query into the computer 102 for communication to the server 134,which may respond with people and/or professional athletes matching thesearch query, as seen in display 3302B. The user may establish a userprofile to identify their friends and/or favorite professional athletesso that the computer 102 may automatically load these individuals, asseen in display 3302C.

Computer 102 may present data for sharing with friends and/or posted toa social networking website. In FIG. 34A, for example, display 3402Aprovides information for sharing, including points, top vertical, totalairtime, and top tempo. As shown in FIG. 34B, display 3402B, forinstance, provides a side by side comparison of performance metrics of auser and an identified friend. In an example, the server 134 may storeperformance metric data on each user and may communicate the data withcomputer 102 of the other user upon request.

FIGS. 35A-B illustrate example displays for comparing a user'sperformance metrics to other individuals in accordance with exampleembodiments. For example, display 3502A may provide a leader board forcomparison of a user's performance metric to friends, selectedprofessional athletes, or all other users including professionalathletes. Example leader boards may be for a top vertical, a top tempo,a total airtime, total games played, total awards won, or for otherperformance metrics. Display 3502B permits a user to view individualswhose performance metrics indicate they are in and are not in aperformance zone (e.g., dunk zone). Computer 102 may also permit theuser to compare their performance metrics to a particular group (e.g.,friends) or to all users.

The foregoing discussion was provided primarily in relation tobasketball, but the above examples may be applied to other team sportsas well as individual sports.

FIG. 36 illustrates a flow diagram of an example method for determiningwhether physical data obtained monitoring a user performing a physicalactivity is within a performance zone in accordance with exampleembodiments. The method of FIG. 36 may be implemented by a computer,such as, for example, the computer 102, server 134, a distributedcomputing system, a cloud computer, other apparatus, and combinationsthereof. The order of the steps shown in FIG. 36 may also be rearranged,additional steps may be included, some steps may be removed, and somesteps may be repeated one or more times. The method may begin at block3602.

In block 3602, the method may include processing input specifying a userattribute. In an example, computer 102 may prompt the user to input onone or more user attributes. Example user attributes may include height,weight, arm length, torso length, leg length, wing span, etc. In anexample, user may specify their body length. Body length may be ameasurement of how high a user can reach one of their hands whilekeeping the opposite foot on the floor.

In block 3604, the method may include adjusting a performance zone basedon the user attribute. In an example, computer 102 may adjust aperformance zone relating to how high a user must jump to dunk abasketball based on one or more of user height, arm length, torsolength, and leg length. For taller users, the performance zone mayspecify a lower minimum jump height to dunk a basketball as comparedwith a minimum jump height required for a smaller user to dunk or reacha basketball rim.

In block 3606, the method may include receiving data generated by asensor. In an example, computer 102 may receive data from at least oneof sensor 304 and 306 during an exercise session in which the userperforms one or more jumps. As discussed above, the data may be rawsignals or may be data processed by the sensors prior to sending tocomputer 102.

In block 3608, the method may include determining whether the data iswithin the performance zone. In an example, computer 102 may processdata received from at least one of sensor 206 and 304 to determine ifany jump performed by the user met or exceeded the minimum jump heightof the performance zone tailored to the user's attributes. For example,computer 102 may determine that a minimum vertical leap of 30 incheswould be required for a user to dunk a basketball, based on the userattributes. Computer 102 may process data received from at least one ofsensor 304 and 306 to determine whether any jump performed by the usermet or exceeded 30 inches. To determine a height of the vertical leap,computer 102 may process data generated by at least one of anaccelerometer and a force sensor, and comparing the data to jump data todetermine that the data is consistent with a jump (e.g., that a usersitting on a chair didn't merely lift their feet off of the ground for apredetermined amount of time). Computer 102 may, in response to thecomparing, process data generated by at least one of an accelerometerand a force sensor to determine a lift off time, a landing time, and aloft time. Computer 102 may calculate vertical leap based on the lofttime.

In block 3610, the method may include outputting the determination. Inan example, computer 102 may output the determination of whether theuser was within the performance zone. The output may be at least one ofaudible and visual. Computer 102 may provide the output immediately upondetecting the user is within the performance zone, or may output thedetermination at some later time (e.g., post workout). The method maythen end, or may return to any of the preceding steps.

Further aspects relate to correlating image data with data relating tophysical activity, such as including, but not limited to, any of the rawand/or processed data disclosed in any of the above embodiments. Datarelating to physical activity (either raw or processed) may be obtained,directly or indirectly, and/or derived from one or more sensors,including those disclosed herein. In accordance with certainembodiments, physical activity data may be overlaid on an image (orsequence of images, e.g., video) of a user, such as user 124, that wascaptured during performance of the physical activity.

FIG. 37 is a flowchart of an example method that may be utilized inaccordance with various embodiments. At exemplary block 3702, image datamay be obtained. Image data may be captured from one or moreimage-capturing devices, such as a camera located on a mobile terminaldevice (see, element 138 of FIG. 1A), a video camera, a still-imagecamera, and/or any apparatus configurable to detect wavelengths ofenergy, including light, magnetic fields, and/or thermal energy. As usedherein, “image data” may encompass raw and/or compressed data, either ina physical tangible form or stored on a computer-readable medium aselectronic information. Further, a plurality of images may form part ofa video. Thus, references to images and/or pictures encompass videos andthe like.

In one embodiment, image data, such as information obtained during theuser's performance of physical activity (e.g., participating in abasketball game and/or performing a specific action, such as dunking aball in a basket), may be captured from one or more devices. Forexample, a computer-readable medium may comprise computer-executableinstructions that, when executed, may perform obtaining a plurality ofimages (e.g. a video) of the athlete playing a sport. For example,mobile terminal 138 may comprise an application that permits user 124(or another user) to use an image capturing device (either part of themobile terminal 138 or provide an input to an external image-capturingdevice, such as camera 126) to capture the image data.

In one embodiment, upon the user activating a record function (which maybe a hard or soft button) on a host device (e.g., the mobile terminal138), the simultaneous capturing of the video and physical activitysensor data may be initiated. In certain embodiments, multiple camerasmay be utilized simultaneously. Multiple cameras may be used, forexample, based upon the user's location, (e.g., through detection of theuser by way of GPS, triangulation, or motion sensors). Image data may beobtained in response to a user operating a camera on a device, such as acamera of mobile terminal 138. In one embodiment, user 124 may providemobile terminal 138 to another individual who can capture video of theuser 124 playing a sport or performing a fitness activity. However, infurther embodiments, one or more cameras may be in a fixed position,angle, focus, and/or combinations thereof. In certain embodiments, imagedata may be obtained from a broadcast source not directly controllableby user 124 (and/or individuals or entities under user's 124 direction),such as for example a content source provider. For example, a contentsource provider may broadcast (either live and/or delayed) a sportingevent. In one embodiment, the event may comprise a scheduled basketballgame. However in another embodiment, sporting event may comprise anunscheduled event, such as a pickup game. In certain embodiments,multiple camera feeds may be utilized to determine which feed(s) orsources of images to use.

In one embodiment, image data may only be captured based on sensor data.In one embodiment, sensor data may be physical activity data. Forexample, in certain implementations, image data may only be capturedupon determining that user is within a “performance zone.” In anotherembodiment, at least one physical attribute value must meet a threshold.Other embodiments may indiscriminately capture image data of user 124,and optional block 3704 or another process may be performed to select aportion of the captured image data. For example, block 3702 may captureover 20 minutes of image data of user 124, however, block 3704 may onlyselect those portions in which the user 124 was in a performance zone.Those skilled in the art will readily appreciate that other selectioncriteria are within the scope of this disclosure.

The image data obtained in block 3702 (and/or selected at block 3704)may be stored on one or more non-transitory computer-readable mediums,such as on server 134, network 132, mobile terminal 138, and/or computer102. The type and/or form of the image data may depend on a myriad offactors, including but not limited to: physical activity data (forexample, as obtained from a sensor), user selection, calibrationparameters, and combinations thereof. Image data may be time stamped.Time stamping of image data may be performed as part of the image data'scollection and/or storage. The time stamp information may comprise a“relative” time stamp that does not depend on the actual time ofcapture, but rather is tied to another event, such as a data point ofactivity data, start time, and/or any other events. In anotherembodiment, an “actual” time stamp may be utilized in which the time ofcapture may or may not be related to another event. Those skilled in theart will appreciate that both types of stamps may be utilized, includingthe utilization of a single actual time stamp that is also correlated toanother event.

At block 3706, physical activity data may be received. As discussedabove in relation to image data, activity data may also be time stamped.In one embodiment, sensor data may be received, which may comprise rawand/or processed information relating to the user's 124 activity.Activity data may be obtained from one or more sensors described herein.For example, in one embodiment, the user's footwear may comprise atleast one sensor. In certain embodiments, at least a portion of theathletic data may remain on the sensory device or another deviceoperatively connected to the user (e.g., wrist-worn device and/orshoe-mounted sensors) until the capturing time period is over. The datamay then be joined as a single file using time stamps. Certainimplementations may store a single file, but transmit a first portion ofthe data (such as the image data) separate from a second portion (suchas the activity data). In another embodiment, a first portion of data(such as the image data) may be stored separate from a second portion(such as the activity data), yet may be transmitted to a first tangiblecomputer-readable medium as a single file.

Multiple sensors (from one or more devices) may be utilized. In oneembodiment, raw accelerometer and/or gyroscope data may be obtained andprocessed. In another embodiment, force sensor data may be received. Inyet another embodiment, physical activity parameters may be calculatedbased upon one or more raw parameters from a plurality of sensors. Asone example, FIG. 9 shows a plurality of data parameters that may beobtained in accordance with certain implementations. In certainembodiments, user 124, the sensor data and/or sensors utilized to obtainthe data (and/or the calculations for providing any processed data) maybe selectable. For example, user 124 (or another input received fromanother source, either manually or automatically) may select a sensor140 associated with shoes and/or other apparel. In this regard, inputsmay not limited to user 124, for example, a coach, trainer, parent,friend, broadcast personnel, and/or any other individual may select oneor more sources for activity data. Further embodiments may calibrate oneor more sensors before utilization of corresponding data. In yet otherembodiments, if calibration parameters are not obtained, data from onemore sensors may be excluded from use. FIG. 10 shows an exemplaryembodiment of calibration; however this disclosure is not limited tothis embodiment. As discussed above in relation to image data, at leasta portion of the physical activity data may be selected for processingand/or utilization.

At block 3708, image data and physical activity data may be correlated.The correlation may be based on the time stamps of the data, such thatphysical activity data is matched to the image data corresponding to thetiming of capture. In yet other embodiments, data may be filtered,processed or otherwise adjusted to be matched with each other. Forexample, each image of a first video, of user 124 performing athleticactivity, may represent 1/20th of a second of the first video, however,data from a first sensor may provide activity data values every ⅕th of asecond, therefore, in one embodiment; four consecutive “frames” of imagedata during the 1/20th of a second may be associated with the sensordata captured during that ⅕ second increment. In yet other embodiments,a plurality of physical activity values may be weighted, averaged, orotherwise adjusted to be associated with a single “frame” or collectiveimage. Correlation of the data may be implemented on one or morecomputer-readable mediums.

Correlation of at least a portion of the data may be implemented on areal-time basis, and/or later in time. Correlation may not occur until aselection of a portion of data is selected. In certain embodiments, thedata may not be correlated until a specific user is selected. Forexample, image and/or physical activity data may be correlated upon thedetermination of a winner of a game, or upon the occurrence of an event(e.g., a user dunking a basketball). Further the type and amount of datato be correlated may also be selectable. For example, upon determining auser dunked a basketball, correlation may be performed on image and/oractivity data that occurred 10 seconds prior to the dunk and continuesto 3 seconds after the dunk. In one embodiment, upon determining that aplayer won a game or event, a larger portion of their data would becorrelated. For example, data covering an entire time frame of a game orevent may be utilized. Further, the data correlated may depend on theevent, data collected, or other variables. For example, for a basketballdunk, activity data collected or derived from one or more force sensorswithin user's shoes may be utilized, yet in a soccer match, arm swingdata may be utilized, alone or in combination with other data, todetermine steps per second, speed, distance, or other parameters.Correlation data may include, but is not limited to: identification ofthe sensing unit, specific sensor, user, time stamp(s), calibrationparameters, confidence values, and combinations thereof.

In further embodiments, system 100 may receive and/or process datagenerated by a sensor, such as a force sensor, to determine a weightdistribution during a performance of an exercise task (e.g., shooting ajump shot in basketball). System 100 may associate a detected weightdistribution, at a time preceding the user input, to determine aninitiation point and/or cessation point for correlation of specificdata. At a subsequent time, system 100 may also process additional userinput indicating unsuccessful completion of the exercise task.

System 100 may process sensor data, such as for example, data receivedfrom the pod sensor 304 and/or the FSR sensor 206 over a session todetermine which data may be classified and/or correlated. For example, auser's hustle during a session may be categorized into two or morecategories. With reference to hustle display 1902B, system 100 maydivide hustle into four categories: walking, jogging, running, andsprinting. With reference to hustle display 1902C, system 100 may dividehustle into three categories: low, medium and high. More or fewercategories of hustle may be defined. System 100 may process the data toidentify a category based on a rate of steps taken by a user perinterval of time (e.g., steps per minute). The correlated physicalactivity data may comprise information indicative of when and/or howoften a user was in each category during a session. In certainembodiments, only physical activity indicative of being within one ormore specific categories may be correlated with the corresponding imagedata.

In certain embodiments, data may be transmitted and displayed on one ormore devices. In certain embodiments, the display device may bephysically distinct from the device which is capturing the image(s)(see, e.g., block 3710). For example, in one embodiment, an individualmay utilize a portable device, such as a mobile terminal, to capture avideo of user 124 performing physical activity, such as participating ina basketball game. Information regarding the captured images may betransmitted (either before or after being correlated with data relatingto the physical activity of user 124) via wired and/or wireless mediums.

FIG. 13, which was discussed above, shows an illustrative example GUIproviding performance metrics during an event, game, or session inaccordance with example embodiments. One or more of these metrics mayrelay information about a length of a current or previous session infield 1304, various performance metrics (e.g., top vertical, totalairtime, tempo, etc.) for the user in field 1308, as well as who theuser played with during the session in field 1310. One or more of thesemetrics may be overlaid with the corresponding imaging data inaccordance with certain embodiments. The image data may be joined toform a video, which may be stored as a single file such that the dataoverlay is part of the video and is displayed with the correspondingvideo portion to which that data was captured. In further embodiments, asecond file may store the data separate from video data.

In one embodiment, image data (and/or the physical activity) data may betransmitted in real-time. One or more images (with the correspondingactivity data) may be displayed on one or more display devices, such asa display at the location of the basketball game, or any other displaymedium, including but not limited to being multi-casted to multipledisplay devices. The images (and correlated data) may be viewed viatelevisions, computing devices, web interfaces, and a combinationthereof. In certain embodiments, user 124 and/or other individuals mayselectively determine which activity data is displayed on one or moredisplay devices. For example, a first viewer may selectively view theuser's current speed and/or average speed, and a second viewer mayselectively view the one or more different activity values, such as forexample, highest vertical jump, number of sprints, average speed, and acombination thereof. In this regard, the data may be formed from, and/orbe updated from a long duration, such as total play time during a game,portion of game (quarter, half, etc.). Thus, there is no requirementthat the image data only be correlated to data obtained during capturingof the image data, but instead may further include (or be derived from)previously-obtained data. Further embodiments may present the imageand/or physical activity data for sharing with friends and/or posting toa social networking website. The transmission of any data may be basedon, at least in part, at least one criterion, such as for example,user-defined criteria that at least a portion of the data meets athreshold. For example, users may only want to upload their bestperformance(s).

Thus, certain embodiments may utilize historical data. As one example,leap data (such as that shown in leap display 1802B) may display auser's jumps chronologically over a session and may indicate a time wheneach jump occurred as well as vertical height for each jump during thesession. The leap display 1802B may also display the user's current dataand/or that user's personal best vertical leap during the event.

Further, as discussed above in relation to the correlation of data, thedisplaying of any data (and/or the selection of what physical activitydata is displayed with the image data) may vary depending on one or morevariables; including, for example, the type of game, event, user's 124selection or input, a viewer's input, an indication that user's 124performance has met a threshold; e.g., reached a performance zone,and/or a combination thereof. Further embodiments may determine, basedon one or more computer-executable instructions on non-transitorycomputer readable mediums, which activity value(s) may be displayed toviewer(s) for a specific time period and the duration of displayingcertain values.

In certain implementations, image data may not be correlated with atleast a portion of activity data until a later time. Transmission and/orcorrelation of image data with activity data may be conducted on aroutine basis, such as every 1 second, 10 seconds, 30 seconds, 1 minute,or any increment of time. In this regard, a system and/or user maydetermine to evaluate one or more metrics at a later time. These metricsmay be based on, for example, a type of athletic activity performed in asession (e.g., basketball game, football game, running session, etc.).Certain embodiments may permit the evaluation and/or analysis ofdifferent metrics than initially viewed and/or desired upon capturingthe image(s). For example, user 124 and/or a coach may be initiallyinterested in evaluating a user's quantity of vertical jumps that meet afirst threshold (e.g., about 4 inches), yet at a later time, the coachor user 124 may want to evaluate the image(s) with an overlay of aquantity of steps per unit time (e.g., number of steps per minute). Incertain embodiments, computer 102 may prompt the user to indicate whichmetrics to monitor for each type of session (e.g., baseball, soccer,basketball, etc.) and store the identified metrics in a user profile. Inyet another embodiment, the type of session may be derived fromcollected data, inclusive, but not limited to, activity data or theimage data.

Computer 102 may also prompt the user for desired metrics at thebeginning of each session for what data to collect—inclusive of datathat may not be overlaid over the image. Further embodiments may adjustthe image data collected and/or utilized. For example, variations mayinclude the resolution, frame rate, storage format protocol, andcombinations thereof. At the beginning of a session, sensors, such assensors within a shoe (see device sensor 140) and/or other sensors, maybe calibrated. Yet in other embodiments, sensors may be calibratedduring, or after, a session or event. In certain embodiments, previouslycollected data may be utilized in determinations of whether to calibrateand/or parameters of calibration.

Block 3710 and/or other aspects of certain embodiments may relate togenerating and/or displaying a summary segment with the image data. Forexample, the image data may be utilized to form a 25 second video. Incertain embodiments, the video file may be formed to include a segment(e.g., 5 seconds), such as located at the end of the 25-seconds of imagedata, that provides a summary of certain statistics. In thoseembodiments, in which the video is a single file, this segment may alsoform part of the same single file. In certain embodiments, this summaryscreen (or another summary) may be presented to the user while the videofile is being created (e.g., during the time in which the image data isbeing properly aligned with the sensor data). Further information may bedisplayed with the image data. For example, in one embodiment, anoverlay may display the origination of the data; such as by a wrist-wornor shoe-mounted sensor, and/or specific manufactures or models ofsensors.

Further aspects relate to creating and/or displaying a “representativeimage” that is formed from an image within the collection of images(see, e.g., block 3712). The representative image may be utilized as a“thumbnail” image or a cover image. In further embodiments, therepresentative image may be used to represent a specific video among aplurality of videos, in which each may have their own representativeimage. In one embodiment, the representative image may be selected basedupon it being correlated in time with a data value that represents thehighest value of at least one athletic parameter. For example, thehighest value of a jump (e.g., vertical height) may be utilized toselect an image. Yet in other embodiments, the highest value relating tovelocity, acceleration, and/or other parameters may be utilized inselecting an image. Those skilled in the art will appreciate that the“best” data value may not be the highest, thus this disclosure is notlimited to image data associated with the “highest” value, but rather isinclusive of any data.

In further embodiments, a user (or any individual) may select whichparameter(s) are desired. In yet other embodiments, computer-executableinstructions on a tangible computer-readable medium may select aparameter based upon the data collected. In yet further embodiments, aplurality of images may be selected based upon the correlated physicalactivity data, and allow the user to select one. Any physical activitydata and/or image data may be associated with location data, such as GPSor a specific court.

Further embodiments relate to creating a collection of image data from aplurality of users, based upon sensed data (see, e.g., block 3714). Inone embodiment, a “highlight reel” may be formed which comprises imagedata of a plurality of users. In one example, a highlight reel may becreated from data obtained from a sporting event. For example, aplurality of players on one or more teams may be recorded, such asduring a televised sporting event. Based upon sensed athletic data,images (e.g., video) obtained during performance of that data may beaggregated to create a highlight reel for the sporting event or aportion thereof (e.g., the first quarter and/or the final two minutes).For example, sensors may obtain athletic data from the players duringthe sporting event, and based upon at least one criterion (i.e., jumpshigher than 24 inches and/or paces greater than 3 steps per second),correlated image data may be utilized in forming the highlight reel.

Certain embodiments relate to generating a feed or a plurality of imagecollections based upon at least one criterion. For example, viewers ofsporting events often do not have the time to watch every game orcompetition, such as during playoffs of sporting events. Thus, in oneembodiment, a feed may be selectively limited to physical activity offriends, teams or athletes followed, basketball games in which certainteam(s) played and a specific player(s) that achieves a specificparameter value(s). Thus, in some embodiments of the invention, imagedata may comprise image data captured during a first time period andimage data captured during a second time period that is different thanthe first time period. These feeds may also be categorized based uponactivity type and/or sensors utilized to capture the activity. Incertain embodiments, the highlight reels and/or feeds may be based, atleast in part, on whether the player(s) are within a performance zone.

In one embodiment, the image data captured during the first time periodis at a first geographic location and image data captured during thesecond time period is at a second geographic location. In certainimplementations, images from two or more locations that are obtainedduring two different time periods, may be combined into a single image.In one embodiment, a user's physical performance may be captured with amobile phone or other device and merged with image data corresponding toa historical athletic performance or known venue. For example, a videoof a user shooting a basketball shot may be merged with a video of afamous athlete shooting a last minute three-point shot. In someembodiments, a user may capture an image of a scene prior to recording avideo of a user performing an athletic move at the same location. Amobile phone, or other device, may then remove the scene data from thevideo to isolate the user. The isolated video of the user may then bemerged with, or overlay, an image or video of another location or event.Similarly, selected portions of captured image data may be replaced. Forexample, a video of a user slam dunking a tennis ball may be edited toreplace the tennis ball with a basketball. Various other features anddevices may be used in accordance with the aspects described herein.Additional or alternative features may also be incorporated into thedevice and/or applications associated therewith.

Conclusion

While the invention has been described with respect to specific examplesincluding presently preferred modes of carrying out the invention, thoseskilled in the art will appreciate that there are numerous variationsand permutations of the above described systems and methods. Forexample, various aspects of the invention may be used in differentcombinations and various different sub-combinations of aspects of theinvention may be used, together, in a single system or method withoutdeparting from the invention. In one example, software and applicationsdescribed herein may be embodied as computer readable instructionsstored in computer readable media. Also, various elements, components,and/or steps described above may be changed, changed in order, omitted,and/or additional elements, components, and/or steps may be addedwithout departing from this invention. Thus, the invention should beconstrued broadly.

1. (canceled)
 2. A computer-implemented method comprising: receiving a first set of physical activity data corresponding to an athletic performance comprising at least a first activity performed by a user, wherein the first set of physical activity data is generated by or derived from a first sensor; capturing, by an image capturing device, image data corresponding to at least the first activity performed by the user; determining, by a processor, that a portion of the physical activity is indicative of the user satisfying a first activity threshold; and transmitting the portion of the physical activity data and the image data to a computing device.
 3. The computer-implemented method of claim 2, further comprising: correlating the image data in accordance with the portion of the first set of physical activity data.
 4. The computer-implemented method of claim 3, wherein the image data comprises a plurality of frames, and wherein the correlating the image data further comprises: associating a first number of frames of the image data with a corresponding time period of the first set of physical activity data.
 5. The computer-implemented method of claim 3, wherein the image data comprises a plurality of frames, the computer-implemented method further comprising: determining, by the processor, a plurality of activity values for a first activity metric corresponding to the portion of the first set of physical activity data; and adjusting the plurality of activity values to be associated with at least a first frame of the image data.
 6. The computer-implemented method of claim 2, further comprising: establishing a communication channel with the first sensor, wherein the first sensor comprises a force sensor; and in response to establishing the communication channel, outputting, to a display device, a communication prompting the user to perform the first activity.
 7. The computer-implemented method of claim 6, further comprising: receiving, from the force sensor, a first set of data relating to the performance of the first activity by the user.
 8. The computer-implemented method of claim 7, wherein the first set of data further comprises at least one of: a shoe type, a shoe color, or a shoe size.
 9. The computer-implemented method of claim 3, further comprising: receiving an input selection identifying the user; and in response to receiving the input selection, initiating the correlation of the image data in accordance with the portion of the first set of physical activity data.
 10. The computer-implemented method of claim 3, further comprising: determining, based on the portion of the first set of physical activity data, a second activity performed by the user; and in response to the determining the second activity, initiating the correlation of the image data in accordance with the portion of the first set of physical activity data.
 11. The computer-implemented method of claim 2, further comprising: receiving a second set of physical activity data corresponding to one or more previous athletic performances where the user performed the first activity; and correlating the image data in accordance with the second set of physical activity data.
 12. One or more non-transitory computer readable media storing instructions that, when executed by at least one processor, cause the at least one processor to: receive a first set of physical activity data corresponding to an athletic performance comprising at least a first activity performed by a user, wherein the first set of physical activity data is generated by or derived from a first sensor; capture, by an image capturing device, image data corresponding to at least the first activity performed by the user; determine that a portion of the physical activity data is indicative of the user satisfying a first activity threshold; correlate the image data in accordance with the portion of the first set of physical activity data; and transmit the portion of the physical activity data and the image data to a computing device.
 13. The one or more non-transitory computer readable media of claim 12, wherein the instructions, when executed, further cause the at least one processor to: receive a second set of physical activity data corresponding to one or more previous athletic performances where the first user performed the first activity; and correlate the image data in accordance with the second set of physical activity data.
 14. The one or more non-transitory computer readable media of claim 12, wherein the instructions, when executed, further cause the at least one processor to: establish a communication channel with the first sensor, wherein the first sensor comprises a force sensor; and in response to establishing the communication channel, output, to a display device, a communication prompting the user to perform the first activity.
 15. The one or more non-transitory computer readable media of claim 14, wherein the instructions, when executed, further cause the at least one processor to: receive, from the force sensor, a first set of data relating to the user performing the first activity. i)
 16. The one or more non-transitory computer readable media of claim 15, wherein the first set of data further comprises at least one of: a shoe type, a shoe color, or a shoe size.
 17. The one or more non-transitory computer readable media of claim 12, wherein the instructions, when executed, further cause the at least one processor to: determine, based on the portion of the first set of physical activity data, a second activity performed by the user; and in response to the determining the second activity, initiate the correlation of the image data in accordance with the portion of the first set of physical activity data.
 18. A computer-implemented method comprising: receiving physical activity data corresponding to an athletic performance for a plurality of players, the physical activity data comprising data generated by or derived from a plurality of sensors; determining, by a processor, that one or more portions of the physical activity data is indicative of one or more players, of the plurality of players, satisfying a first athletic performance criterion; capturing, by an image capturing device, image data relating to the athletic performance; correlating the captured image data with the corresponding one or more portions of the physical activity data; aggregating the image data and the correlated one or more portions of the physical activity data to generate a highlight reel of the athletic performance; and transmitting the highlight reel to a computing device.
 19. The computer-implemented method of claim 18, further comprising: receiving an input selection identifying at least a first player of the plurality of players; and in response to receiving the input selection, initiating the correlation of the captured image data with the corresponding one or more portions of the physical activity data.
 20. The computer-implemented method of claim 18, wherein the image data comprises a plurality of frames, the computer-implemented method further comprising: determining a plurality of activity values for a first activity metric corresponding to the one or more portions of the physical activity data; and adjusting the plurality of activity values to be associated with at least a first frame of the image data.
 21. The computer-implemented method of claim 18, wherein the image data comprises a plurality of frames, and wherein the correlating the image data further comprises: associating a first number of frames of the image data with a corresponding time period of a first portion, of the one or more portions, of the physical activity data. 